Overview

Brought to you by YData

Dataset statistics

Number of variables31
Number of observations30189
Missing cells71867
Missing cells (%)7.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.1 MiB
Average record size in memory248.0 B

Variable types

Categorical8
Numeric9
Text13
DateTime1

Alerts

finishing_position is highly overall correlated with running_position_4 and 2 other fieldsHigh correlation
race_course is highly overall correlated with trackHigh correlation
running_position_1 is highly overall correlated with running_position_2 and 1 other fieldsHigh correlation
running_position_2 is highly overall correlated with running_position_1 and 1 other fieldsHigh correlation
running_position_3 is highly overall correlated with running_position_1 and 1 other fieldsHigh correlation
running_position_4 is highly overall correlated with finishing_positionHigh correlation
running_position_5 is highly overall correlated with finishing_positionHigh correlation
running_position_6 is highly overall correlated with finishing_positionHigh correlation
track is highly overall correlated with race_courseHigh correlation
track_condition is highly imbalanced (53.4%) Imbalance
horse_number has 338 (1.1%) missing values Missing
running_position_1 has 615 (2.0%) missing values Missing
running_position_2 has 629 (2.1%) missing values Missing
running_position_3 has 647 (2.1%) missing values Missing
running_position_4 has 13571 (45.0%) missing values Missing
running_position_5 has 26425 (87.5%) missing values Missing
running_position_6 has 29640 (98.2%) missing values Missing

Reproduction

Analysis started2025-01-11 06:53:00.988590
Analysis finished2025-01-11 06:53:14.135514
Duration13.15 seconds
Software versionydata-profiling vv4.12.1
Download configurationconfig.json

Variables

finishing_position
Categorical

High correlation 

Distinct36
Distinct (%)0.1%
Missing2
Missing (%)< 0.1%
Memory size236.0 KiB
1
2361 
2
2354 
3
2350 
6
2346 
5
2341 
Other values (31)
18435 

Length

Max length5
Median length1
Mean length1.3208335
Min length1

Characters and Unicode

Total characters39872
Distinct characters28
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row1
2nd row2
3rd row3
4th row4
5th row5

Common Values

ValueCountFrequency (%)
1 2361
 
7.8%
2 2354
 
7.8%
3 2350
 
7.8%
6 2346
 
7.8%
5 2341
 
7.8%
4 2340
 
7.8%
7 2339
 
7.7%
8 2329
 
7.7%
9 2305
 
7.6%
10 2260
 
7.5%
Other values (26) 6862
22.7%

Length

2025-01-11T12:23:14.224111image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
4 2375
 
7.8%
1 2373
 
7.8%
3 2370
 
7.8%
2 2368
 
7.8%
6 2360
 
7.8%
5 2359
 
7.8%
7 2347
 
7.7%
8 2341
 
7.7%
9 2313
 
7.6%
10 2268
 
7.5%
Other values (15) 6868
22.6%

Most occurring characters

ValueCountFrequency (%)
1 12876
32.3%
2 4390
 
11.0%
3 3365
 
8.4%
4 3213
 
8.1%
6 2360
 
5.9%
5 2359
 
5.9%
7 2347
 
5.9%
8 2341
 
5.9%
9 2313
 
5.8%
0 2268
 
5.7%
Other values (18) 2040
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 37832
94.9%
Uppercase Letter 1773
 
4.4%
Space Separator 155
 
0.4%
Dash Punctuation 112
 
0.3%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
W 589
33.2%
V 563
31.8%
D 163
 
9.2%
H 155
 
8.7%
A 112
 
6.3%
U 55
 
3.1%
P 35
 
2.0%
R 26
 
1.5%
X 26
 
1.5%
F 17
 
1.0%
Other values (6) 32
 
1.8%
Decimal Number
ValueCountFrequency (%)
1 12876
34.0%
2 4390
 
11.6%
3 3365
 
8.9%
4 3213
 
8.5%
6 2360
 
6.2%
5 2359
 
6.2%
7 2347
 
6.2%
8 2341
 
6.2%
9 2313
 
6.1%
0 2268
 
6.0%
Space Separator
ValueCountFrequency (%)
155
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 112
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 38099
95.6%
Latin 1773
 
4.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
W 589
33.2%
V 563
31.8%
D 163
 
9.2%
H 155
 
8.7%
A 112
 
6.3%
U 55
 
3.1%
P 35
 
2.0%
R 26
 
1.5%
X 26
 
1.5%
F 17
 
1.0%
Other values (6) 32
 
1.8%
Common
ValueCountFrequency (%)
1 12876
33.8%
2 4390
 
11.5%
3 3365
 
8.8%
4 3213
 
8.4%
6 2360
 
6.2%
5 2359
 
6.2%
7 2347
 
6.2%
8 2341
 
6.1%
9 2313
 
6.1%
0 2268
 
6.0%
Other values (2) 267
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 39872
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 12876
32.3%
2 4390
 
11.0%
3 3365
 
8.4%
4 3213
 
8.1%
6 2360
 
5.9%
5 2359
 
5.9%
7 2347
 
5.9%
8 2341
 
5.9%
9 2313
 
5.8%
0 2268
 
5.7%
Other values (18) 2040
 
5.1%

horse_number
Real number (ℝ)

Missing 

Distinct14
Distinct (%)< 0.1%
Missing338
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean6.8853975
Minimum1
Maximum14
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size236.0 KiB
2025-01-11T12:23:14.332979image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median7
Q310
95-th percentile13
Maximum14
Range13
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.751176
Coefficient of variation (CV)0.54480166
Kurtosis-1.1097322
Mean6.8853975
Median Absolute Deviation (MAD)3
Skewness0.090320115
Sum205536
Variance14.071321
MonotonicityNot monotonic
2025-01-11T12:23:14.439528image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
1 2367
 
7.8%
2 2367
 
7.8%
3 2367
 
7.8%
5 2367
 
7.8%
4 2367
 
7.8%
6 2365
 
7.8%
7 2355
 
7.8%
8 2342
 
7.8%
9 2322
 
7.7%
10 2284
 
7.6%
Other values (4) 6348
21.0%
ValueCountFrequency (%)
1 2367
7.8%
2 2367
7.8%
3 2367
7.8%
4 2367
7.8%
5 2367
7.8%
6 2365
7.8%
7 2355
7.8%
8 2342
7.8%
9 2322
7.7%
10 2284
7.6%
ValueCountFrequency (%)
14 958
3.2%
13 1019
3.4%
12 2142
7.1%
11 2229
7.4%
10 2284
7.6%
9 2322
7.7%
8 2342
7.8%
7 2355
7.8%
6 2365
7.8%
5 2367
7.8%
Distinct2162
Distinct (%)7.2%
Missing0
Missing (%)0.0%
Memory size236.0 KiB
2025-01-11T12:23:14.707583image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length18
Median length14
Mean length12.193249
Min length3

Characters and Unicode

Total characters368102
Distinct characters29
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique157 ?
Unique (%)0.5%

Sample

1st rowDOUBLE DRAGON
2nd rowPLAIN BLUE BANNER
3rd rowGOLDWEAVER
4th rowSUPREME PROFIT
5th rowTHE ONLY KID
ValueCountFrequency (%)
happy 673
 
1.1%
dragon 622
 
1.0%
star 611
 
1.0%
king 588
 
1.0%
lucky 571
 
0.9%
the 570
 
0.9%
of 516
 
0.9%
super 443
 
0.7%
win 438
 
0.7%
boy 427
 
0.7%
Other values (1947) 55202
91.0%
2025-01-11T12:23:15.075409image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 35248
 
9.6%
30472
 
8.3%
A 28190
 
7.7%
R 26726
 
7.3%
I 24494
 
6.7%
N 24260
 
6.6%
O 23620
 
6.4%
T 19951
 
5.4%
L 18391
 
5.0%
S 18220
 
4.9%
Other values (19) 118530
32.2%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 336691
91.5%
Space Separator 30472
 
8.3%
Other Punctuation 742
 
0.2%
Dash Punctuation 197
 
0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 35248
 
10.5%
A 28190
 
8.4%
R 26726
 
7.9%
I 24494
 
7.3%
N 24260
 
7.2%
O 23620
 
7.0%
T 19951
 
5.9%
L 18391
 
5.5%
S 18220
 
5.4%
G 12716
 
3.8%
Other values (16) 104875
31.1%
Space Separator
ValueCountFrequency (%)
30472
100.0%
Other Punctuation
ValueCountFrequency (%)
' 742
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 197
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 336691
91.5%
Common 31411
 
8.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 35248
 
10.5%
A 28190
 
8.4%
R 26726
 
7.9%
I 24494
 
7.3%
N 24260
 
7.2%
O 23620
 
7.0%
T 19951
 
5.9%
L 18391
 
5.5%
S 18220
 
5.4%
G 12716
 
3.8%
Other values (16) 104875
31.1%
Common
ValueCountFrequency (%)
30472
97.0%
' 742
 
2.4%
- 197
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 368102
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
E 35248
 
9.6%
30472
 
8.3%
A 28190
 
7.7%
R 26726
 
7.3%
I 24494
 
6.7%
N 24260
 
6.6%
O 23620
 
6.4%
T 19951
 
5.4%
L 18391
 
5.0%
S 18220
 
4.9%
Other values (19) 118530
32.2%
Distinct2162
Distinct (%)7.2%
Missing0
Missing (%)0.0%
Memory size236.0 KiB
2025-01-11T12:23:15.373534image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters120756
Distinct characters21
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique157 ?
Unique (%)0.5%

Sample

1st rowK019
2nd rowS070
3rd rowP072
4th rowP230
5th rowH173
ValueCountFrequency (%)
s205 51
 
0.2%
p272 50
 
0.2%
s023 47
 
0.2%
n409 47
 
0.2%
p422 45
 
0.1%
s138 45
 
0.1%
p310 44
 
0.1%
p423 44
 
0.1%
t099 44
 
0.1%
p151 43
 
0.1%
Other values (2152) 29729
98.5%
2025-01-11T12:23:15.779349image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13745
11.4%
2 13208
10.9%
3 12801
10.6%
0 12442
10.3%
4 9160
 
7.6%
S 7485
 
6.2%
T 7009
 
5.8%
8 6133
 
5.1%
5 5914
 
4.9%
9 5892
 
4.9%
Other values (11) 26967
22.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 90567
75.0%
Uppercase Letter 30189
 
25.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 7485
24.8%
T 7009
23.2%
P 5602
18.6%
V 4263
14.1%
N 2957
 
9.8%
A 1238
 
4.1%
M 1085
 
3.6%
L 379
 
1.3%
K 155
 
0.5%
J 10
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
1 13745
15.2%
2 13208
14.6%
3 12801
14.1%
0 12442
13.7%
4 9160
10.1%
8 6133
6.8%
5 5914
6.5%
9 5892
6.5%
6 5776
6.4%
7 5496
 
6.1%

Most occurring scripts

ValueCountFrequency (%)
Common 90567
75.0%
Latin 30189
 
25.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 7485
24.8%
T 7009
23.2%
P 5602
18.6%
V 4263
14.1%
N 2957
 
9.8%
A 1238
 
4.1%
M 1085
 
3.6%
L 379
 
1.3%
K 155
 
0.5%
J 10
 
< 0.1%
Common
ValueCountFrequency (%)
1 13745
15.2%
2 13208
14.6%
3 12801
14.1%
0 12442
13.7%
4 9160
10.1%
8 6133
6.8%
5 5914
6.5%
9 5892
6.5%
6 5776
6.4%
7 5496
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 120756
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 13745
11.4%
2 13208
10.9%
3 12801
10.6%
0 12442
10.3%
4 9160
 
7.6%
S 7485
 
6.2%
T 7009
 
5.8%
8 6133
 
5.1%
5 5914
 
4.9%
9 5892
 
4.9%
Other values (11) 26967
22.3%

jockey
Text

Distinct106
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size236.0 KiB
2025-01-11T12:23:15.954664image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length12
Median length11
Mean length8.2804664
Min length3

Characters and Unicode

Total characters249979
Distinct characters52
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)0.1%

Sample

1st rowB Prebble
2nd rowD Whyte
3rd rowY T Cheng
4th rowJ Moreira
5th rowZ Purton
ValueCountFrequency (%)
k 6098
 
8.5%
c 5835
 
8.1%
n 3628
 
5.0%
h 3517
 
4.9%
m 3229
 
4.5%
y 2440
 
3.4%
t 2184
 
3.0%
j 2016
 
2.8%
moreira 1995
 
2.8%
d 1801
 
2.5%
Other values (120) 39338
54.6%
2025-01-11T12:23:16.222003image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
41892
16.8%
e 20502
 
8.2%
o 14723
 
5.9%
n 12611
 
5.0%
a 12016
 
4.8%
C 10469
 
4.2%
r 10367
 
4.1%
i 10233
 
4.1%
l 10129
 
4.1%
u 7243
 
2.9%
Other values (42) 99794
39.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 136301
54.5%
Uppercase Letter 71693
28.7%
Space Separator 41892
 
16.8%
Dash Punctuation 89
 
< 0.1%
Other Punctuation 4
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 20502
15.0%
o 14723
10.8%
n 12611
9.3%
a 12016
8.8%
r 10367
 
7.6%
i 10233
 
7.5%
l 10129
 
7.4%
u 7243
 
5.3%
g 6696
 
4.9%
t 5829
 
4.3%
Other values (15) 25952
19.0%
Uppercase Letter
ValueCountFrequency (%)
C 10469
14.6%
M 6592
 
9.2%
K 6103
 
8.5%
H 5070
 
7.1%
L 4929
 
6.9%
T 4530
 
6.3%
N 4485
 
6.3%
W 4124
 
5.8%
Y 3856
 
5.4%
S 3678
 
5.1%
Other values (14) 17857
24.9%
Space Separator
ValueCountFrequency (%)
41892
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 89
100.0%
Other Punctuation
ValueCountFrequency (%)
' 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 207994
83.2%
Common 41985
 
16.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 20502
 
9.9%
o 14723
 
7.1%
n 12611
 
6.1%
a 12016
 
5.8%
C 10469
 
5.0%
r 10367
 
5.0%
i 10233
 
4.9%
l 10129
 
4.9%
u 7243
 
3.5%
g 6696
 
3.2%
Other values (39) 93005
44.7%
Common
ValueCountFrequency (%)
41892
99.8%
- 89
 
0.2%
' 4
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 249979
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
41892
16.8%
e 20502
 
8.2%
o 14723
 
5.9%
n 12611
 
5.0%
a 12016
 
4.8%
C 10469
 
4.2%
r 10367
 
4.1%
i 10233
 
4.1%
l 10129
 
4.1%
u 7243
 
2.9%
Other values (42) 99794
39.9%
Distinct95
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size236.0 KiB
2025-01-11T12:23:16.358238image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length14
Median length13
Mean length7.682169
Min length4

Characters and Unicode

Total characters231917
Distinct characters49
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)0.1%

Sample

1st rowD Cruz
2nd rowD E Ferraris
3rd rowY S Tsui
4th rowC S Shum
5th rowK W Lui
ValueCountFrequency (%)
c 6029
 
7.6%
s 5382
 
6.8%
a 4797
 
6.1%
j 4251
 
5.4%
p 3876
 
4.9%
w 3710
 
4.7%
d 3360
 
4.2%
t 3332
 
4.2%
k 3194
 
4.0%
y 3098
 
3.9%
Other values (107) 38073
48.1%
2025-01-11T12:23:16.599058image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
48913
21.1%
i 12331
 
5.3%
S 11492
 
5.0%
u 11405
 
4.9%
C 9934
 
4.3%
o 9651
 
4.2%
r 9576
 
4.1%
e 8571
 
3.7%
n 7795
 
3.4%
Y 7465
 
3.2%
Other values (39) 94784
40.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 101494
43.8%
Uppercase Letter 80304
34.6%
Space Separator 48913
21.1%
Other Punctuation 1203
 
0.5%
Dash Punctuation 3
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 12331
12.1%
u 11405
11.2%
o 9651
9.5%
r 9576
9.4%
e 8571
8.4%
n 7795
7.7%
a 7452
7.3%
l 7291
7.2%
s 6252
 
6.2%
z 4761
 
4.7%
Other values (14) 16409
16.2%
Uppercase Letter
ValueCountFrequency (%)
S 11492
14.3%
C 9934
12.4%
Y 7465
 
9.3%
T 4989
 
6.2%
A 4800
 
6.0%
L 4673
 
5.8%
F 4404
 
5.5%
M 4361
 
5.4%
J 4251
 
5.3%
W 4226
 
5.3%
Other values (12) 19709
24.5%
Space Separator
ValueCountFrequency (%)
48913
100.0%
Other Punctuation
ValueCountFrequency (%)
' 1203
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 181798
78.4%
Common 50119
 
21.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 12331
 
6.8%
S 11492
 
6.3%
u 11405
 
6.3%
C 9934
 
5.5%
o 9651
 
5.3%
r 9576
 
5.3%
e 8571
 
4.7%
n 7795
 
4.3%
Y 7465
 
4.1%
a 7452
 
4.1%
Other values (36) 86126
47.4%
Common
ValueCountFrequency (%)
48913
97.6%
' 1203
 
2.4%
- 3
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 231917
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
48913
21.1%
i 12331
 
5.3%
S 11492
 
5.0%
u 11405
 
4.9%
C 9934
 
4.3%
o 9651
 
4.2%
r 9576
 
4.1%
e 8571
 
3.7%
n 7795
 
3.4%
Y 7465
 
3.2%
Other values (39) 94784
40.9%

actual_weight
Categorical

Distinct32
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size236.0 KiB
126
 
2057
133
 
1951
123
 
1739
125
 
1738
120
 
1605
Other values (27)
21099 

Length

Max length3
Median length3
Mean length2.9998675
Min length1

Characters and Unicode

Total characters90563
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row133
2nd row133
3rd row121
4th row132
5th row125

Common Values

ValueCountFrequency (%)
126 2057
 
6.8%
133 1951
 
6.5%
123 1739
 
5.8%
125 1738
 
5.8%
120 1605
 
5.3%
122 1490
 
4.9%
121 1469
 
4.9%
124 1437
 
4.8%
127 1373
 
4.5%
128 1356
 
4.5%
Other values (22) 13974
46.3%

Length

2025-01-11T12:23:16.725309image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
126 2057
 
6.8%
133 1951
 
6.5%
123 1739
 
5.8%
125 1738
 
5.8%
120 1605
 
5.3%
122 1490
 
4.9%
121 1469
 
4.9%
124 1437
 
4.8%
127 1373
 
4.5%
128 1356
 
4.5%
Other values (22) 13974
46.3%

Most occurring characters

ValueCountFrequency (%)
1 42040
46.4%
2 18378
20.3%
3 10015
 
11.1%
0 3483
 
3.8%
6 3263
 
3.6%
5 2950
 
3.3%
8 2790
 
3.1%
9 2660
 
2.9%
7 2627
 
2.9%
4 2355
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 90561
> 99.9%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 42040
46.4%
2 18378
20.3%
3 10015
 
11.1%
0 3483
 
3.8%
6 3263
 
3.6%
5 2950
 
3.3%
8 2790
 
3.1%
9 2660
 
2.9%
7 2627
 
2.9%
4 2355
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 90563
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 42040
46.4%
2 18378
20.3%
3 10015
 
11.1%
0 3483
 
3.8%
6 3263
 
3.6%
5 2950
 
3.3%
8 2790
 
3.1%
9 2660
 
2.9%
7 2627
 
2.9%
4 2355
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90563
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 42040
46.4%
2 18378
20.3%
3 10015
 
11.1%
0 3483
 
3.8%
6 3263
 
3.6%
5 2950
 
3.3%
8 2790
 
3.1%
9 2660
 
2.9%
7 2627
 
2.9%
4 2355
 
2.6%
Distinct399
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size236.0 KiB
2025-01-11T12:23:16.998487image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length4
Mean length3.9573355
Min length1

Characters and Unicode

Total characters119468
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)0.1%

Sample

1st row1032
2nd row1075
3rd row1065
4th row1222
5th row1136
ValueCountFrequency (%)
1088 229
 
0.8%
1094 222
 
0.7%
1089 217
 
0.7%
1106 217
 
0.7%
1108 214
 
0.7%
1097 212
 
0.7%
1102 212
 
0.7%
1093 212
 
0.7%
1092 210
 
0.7%
1099 206
 
0.7%
Other values (389) 28038
92.9%
2025-01-11T12:23:17.393538image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 49136
41.1%
0 18652
 
15.6%
2 8048
 
6.7%
9 7099
 
5.9%
8 6302
 
5.3%
6 6200
 
5.2%
4 5997
 
5.0%
3 5990
 
5.0%
5 5976
 
5.0%
7 5965
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 119365
99.9%
Dash Punctuation 103
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 49136
41.2%
0 18652
 
15.6%
2 8048
 
6.7%
9 7099
 
5.9%
8 6302
 
5.3%
6 6200
 
5.2%
4 5997
 
5.0%
3 5990
 
5.0%
5 5976
 
5.0%
7 5965
 
5.0%
Dash Punctuation
ValueCountFrequency (%)
- 103
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 119468
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 49136
41.1%
0 18652
 
15.6%
2 8048
 
6.7%
9 7099
 
5.9%
8 6302
 
5.3%
6 6200
 
5.2%
4 5997
 
5.0%
3 5990
 
5.0%
5 5976
 
5.0%
7 5965
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 119468
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 49136
41.1%
0 18652
 
15.6%
2 8048
 
6.7%
9 7099
 
5.9%
8 6302
 
5.3%
6 6200
 
5.2%
4 5997
 
5.0%
3 5990
 
5.0%
5 5976
 
5.0%
7 5965
 
5.0%

draw
Categorical

Distinct16
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size236.0 KiB
3
2363 
2
2357 
4
2357 
5
2357 
1
2356 
Other values (11)
18399 

Length

Max length3
Median length1
Mean length1.319686
Min length1

Characters and Unicode

Total characters39840
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row1
2nd row13
3rd row3
4th row2
5th row9

Common Values

ValueCountFrequency (%)
3 2363
 
7.8%
2 2357
 
7.8%
4 2357
 
7.8%
5 2357
 
7.8%
1 2356
 
7.8%
6 2355
 
7.8%
7 2346
 
7.8%
8 2330
 
7.7%
9 2308
 
7.6%
10 2255
 
7.5%
Other values (6) 6805
22.5%

Length

2025-01-11T12:23:17.524313image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
3 2363
 
7.8%
2 2357
 
7.8%
4 2357
 
7.8%
5 2357
 
7.8%
1 2356
 
7.8%
6 2355
 
7.8%
7 2346
 
7.8%
8 2330
 
7.7%
9 2308
 
7.6%
10 2255
 
7.5%
Other values (6) 6805
22.5%

Most occurring characters

ValueCountFrequency (%)
1 13023
32.7%
2 4449
 
11.2%
3 3365
 
8.4%
4 3278
 
8.2%
5 2358
 
5.9%
6 2355
 
5.9%
7 2346
 
5.9%
8 2330
 
5.8%
9 2308
 
5.8%
0 2255
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 38067
95.5%
Dash Punctuation 1773
 
4.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13023
34.2%
2 4449
 
11.7%
3 3365
 
8.8%
4 3278
 
8.6%
5 2358
 
6.2%
6 2355
 
6.2%
7 2346
 
6.2%
8 2330
 
6.1%
9 2308
 
6.1%
0 2255
 
5.9%
Dash Punctuation
ValueCountFrequency (%)
- 1773
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 39840
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 13023
32.7%
2 4449
 
11.2%
3 3365
 
8.4%
4 3278
 
8.2%
5 2358
 
5.9%
6 2355
 
5.9%
7 2346
 
5.9%
8 2330
 
5.8%
9 2308
 
5.8%
0 2255
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 39840
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 13023
32.7%
2 4449
 
11.2%
3 3365
 
8.4%
4 3278
 
8.2%
5 2358
 
5.9%
6 2355
 
5.9%
7 2346
 
5.9%
8 2330
 
5.8%
9 2308
 
5.8%
0 2255
 
5.7%
Distinct217
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size236.0 KiB
2025-01-11T12:23:17.732833image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length6
Median length5
Mean length3.7195005
Min length1

Characters and Unicode

Total characters112288
Distinct characters22
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique57 ?
Unique (%)0.2%

Sample

1st row-
2nd row2
3rd row2
4th row2
5th row4-1/4
ValueCountFrequency (%)
3042
 
10.1%
3-1/2 888
 
2.9%
2-3/4 886
 
2.9%
3 882
 
2.9%
2-1/4 877
 
2.9%
3-1/4 873
 
2.9%
4-1/4 872
 
2.9%
2-1/2 864
 
2.9%
2 845
 
2.8%
3-3/4 827
 
2.7%
Other values (203) 19333
64.0%
2025-01-11T12:23:18.058109image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 22839
20.3%
/ 19794
17.6%
1 19425
17.3%
4 16639
14.8%
2 11109
9.9%
3 10588
9.4%
5 2850
 
2.5%
6 2311
 
2.1%
7 1820
 
1.6%
8 1376
 
1.2%
Other values (12) 3537
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 67941
60.5%
Dash Punctuation 22839
 
20.3%
Other Punctuation 19794
 
17.6%
Uppercase Letter 1711
 
1.5%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 19425
28.6%
4 16639
24.5%
2 11109
16.4%
3 10588
15.6%
5 2850
 
4.2%
6 2311
 
3.4%
7 1820
 
2.7%
8 1376
 
2.0%
9 1067
 
1.6%
0 756
 
1.1%
Uppercase Letter
ValueCountFrequency (%)
N 578
33.8%
H 452
26.4%
S 372
21.7%
D 151
 
8.8%
O 72
 
4.2%
E 71
 
4.1%
M 7
 
0.4%
L 7
 
0.4%
T 1
 
0.1%
Dash Punctuation
ValueCountFrequency (%)
- 22839
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 19794
100.0%
Math Symbol
ValueCountFrequency (%)
+ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 110577
98.5%
Latin 1711
 
1.5%

Most frequent character per script

Common
ValueCountFrequency (%)
- 22839
20.7%
/ 19794
17.9%
1 19425
17.6%
4 16639
15.0%
2 11109
10.0%
3 10588
9.6%
5 2850
 
2.6%
6 2311
 
2.1%
7 1820
 
1.6%
8 1376
 
1.2%
Other values (3) 1826
 
1.7%
Latin
ValueCountFrequency (%)
N 578
33.8%
H 452
26.4%
S 372
21.7%
D 151
 
8.8%
O 72
 
4.2%
E 71
 
4.1%
M 7
 
0.4%
L 7
 
0.4%
T 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 112288
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 22839
20.3%
/ 19794
17.6%
1 19425
17.3%
4 16639
14.8%
2 11109
9.9%
3 10588
9.4%
5 2850
 
2.5%
6 2311
 
2.1%
7 1820
 
1.6%
8 1376
 
1.2%
Other values (12) 3537
 
3.1%

running_position_1
Real number (ℝ)

High correlation  Missing 

Distinct14
Distinct (%)< 0.1%
Missing615
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean6.833942
Minimum1
Maximum14
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size236.0 KiB
2025-01-11T12:23:18.164741image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median7
Q310
95-th percentile13
Maximum14
Range13
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.7272671
Coefficient of variation (CV)0.54540514
Kurtosis-1.10225
Mean6.833942
Median Absolute Deviation (MAD)3
Skewness0.09733024
Sum202107
Variance13.89252
MonotonicityNot monotonic
2025-01-11T12:23:18.262363image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
1 2367
 
7.8%
2 2367
 
7.8%
4 2367
 
7.8%
3 2367
 
7.8%
5 2366
 
7.8%
6 2363
 
7.8%
7 2353
 
7.8%
8 2339
 
7.7%
9 2316
 
7.7%
10 2270
 
7.5%
Other values (4) 6099
20.2%
ValueCountFrequency (%)
1 2367
7.8%
2 2367
7.8%
3 2367
7.8%
4 2367
7.8%
5 2366
7.8%
6 2363
7.8%
7 2353
7.8%
8 2339
7.7%
9 2316
7.7%
10 2270
7.5%
ValueCountFrequency (%)
14 856
 
2.8%
13 1000
3.3%
12 2045
6.8%
11 2198
7.3%
10 2270
7.5%
9 2316
7.7%
8 2339
7.7%
7 2353
7.8%
6 2363
7.8%
5 2366
7.8%

running_position_2
Real number (ℝ)

High correlation  Missing 

Distinct14
Distinct (%)< 0.1%
Missing629
Missing (%)2.1%
Infinite0
Infinite (%)0.0%
Mean6.8313261
Minimum1
Maximum14
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size236.0 KiB
2025-01-11T12:23:18.356601image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median7
Q310
95-th percentile13
Maximum14
Range13
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.7259326
Coefficient of variation (CV)0.54541864
Kurtosis-1.1018679
Mean6.8313261
Median Absolute Deviation (MAD)3
Skewness0.09758983
Sum201934
Variance13.882574
MonotonicityNot monotonic
2025-01-11T12:23:18.454395image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
2 2367
 
7.8%
1 2367
 
7.8%
3 2367
 
7.8%
5 2367
 
7.8%
4 2366
 
7.8%
6 2363
 
7.8%
7 2352
 
7.8%
8 2339
 
7.7%
9 2316
 
7.7%
10 2270
 
7.5%
Other values (4) 6086
20.2%
ValueCountFrequency (%)
1 2367
7.8%
2 2367
7.8%
3 2367
7.8%
4 2366
7.8%
5 2367
7.8%
6 2363
7.8%
7 2352
7.8%
8 2339
7.7%
9 2316
7.7%
10 2270
7.5%
ValueCountFrequency (%)
14 851
 
2.8%
13 998
3.3%
12 2040
6.8%
11 2197
7.3%
10 2270
7.5%
9 2316
7.7%
8 2339
7.7%
7 2352
7.8%
6 2363
7.8%
5 2367
7.8%

running_position_3
Real number (ℝ)

High correlation  Missing 

Distinct14
Distinct (%)< 0.1%
Missing647
Missing (%)2.1%
Infinite0
Infinite (%)0.0%
Mean6.8269921
Minimum1
Maximum14
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size236.0 KiB
2025-01-11T12:23:18.679125image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median7
Q310
95-th percentile13
Maximum14
Range13
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.724886
Coefficient of variation (CV)0.54561159
Kurtosis-1.101657
Mean6.8269921
Median Absolute Deviation (MAD)3
Skewness0.098363314
Sum201683
Variance13.874776
MonotonicityNot monotonic
2025-01-11T12:23:18.777826image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
4 2371
 
7.9%
1 2369
 
7.8%
2 2368
 
7.8%
3 2368
 
7.8%
5 2363
 
7.8%
6 2359
 
7.8%
7 2351
 
7.8%
8 2341
 
7.8%
9 2314
 
7.7%
10 2269
 
7.5%
Other values (4) 6069
20.1%
ValueCountFrequency (%)
1 2369
7.8%
2 2368
7.8%
3 2368
7.8%
4 2371
7.9%
5 2363
7.8%
6 2359
7.8%
7 2351
7.8%
8 2341
7.8%
9 2314
7.7%
10 2269
7.5%
ValueCountFrequency (%)
14 845
 
2.8%
13 998
3.3%
12 2030
6.7%
11 2196
7.3%
10 2269
7.5%
9 2314
7.7%
8 2341
7.8%
7 2351
7.8%
6 2359
7.8%
5 2363
7.8%

running_position_4
Real number (ℝ)

High correlation  Missing 

Distinct14
Distinct (%)0.1%
Missing13571
Missing (%)45.0%
Infinite0
Infinite (%)0.0%
Mean6.942472
Minimum1
Maximum14
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size236.0 KiB
2025-01-11T12:23:18.872693image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median7
Q310
95-th percentile13
Maximum14
Range13
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.7980795
Coefficient of variation (CV)0.54707883
Kurtosis-1.1138139
Mean6.942472
Median Absolute Deviation (MAD)3
Skewness0.098076577
Sum115370
Variance14.425408
MonotonicityNot monotonic
2025-01-11T12:23:18.973973image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
4 1314
 
4.4%
1 1312
 
4.3%
3 1310
 
4.3%
2 1309
 
4.3%
6 1304
 
4.3%
5 1304
 
4.3%
7 1301
 
4.3%
8 1293
 
4.3%
9 1279
 
4.2%
10 1249
 
4.1%
Other values (4) 3643
 
12.1%
(Missing) 13571
45.0%
ValueCountFrequency (%)
1 1312
4.3%
2 1309
4.3%
3 1310
4.3%
4 1314
4.4%
5 1304
4.3%
6 1304
4.3%
7 1301
4.3%
8 1293
4.3%
9 1279
4.2%
10 1249
4.1%
ValueCountFrequency (%)
14 609
2.0%
13 721
2.4%
12 1116
3.7%
11 1197
4.0%
10 1249
4.1%
9 1279
4.2%
8 1293
4.3%
7 1301
4.3%
6 1304
4.3%
5 1304
4.3%
Distinct4175
Distinct (%)13.8%
Missing0
Missing (%)0.0%
Memory size236.0 KiB
2025-01-11T12:23:19.198669image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.9113584
Min length3

Characters and Unicode

Total characters208647
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1109 ?
Unique (%)3.7%

Sample

1st row1.22.33
2nd row1.22.65
3rd row1.22.66
4th row1.22.66
5th row1.23.02
ValueCountFrequency (%)
669
 
2.2%
1.10.72 59
 
0.2%
1.10.37 58
 
0.2%
1.10.42 56
 
0.2%
1.10.45 56
 
0.2%
1.10.64 55
 
0.2%
1.10.21 55
 
0.2%
1.10.50 55
 
0.2%
1.10.43 53
 
0.2%
1.10.47 53
 
0.2%
Other values (4165) 29020
96.1%
2025-01-11T12:23:19.553068image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 59040
28.3%
1 43528
20.9%
0 18417
 
8.8%
2 16192
 
7.8%
4 12867
 
6.2%
3 12251
 
5.9%
5 11383
 
5.5%
9 9513
 
4.6%
8 8221
 
3.9%
7 7772
 
3.7%
Other values (2) 9463
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147600
70.7%
Other Punctuation 59040
 
28.3%
Dash Punctuation 2007
 
1.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 43528
29.5%
0 18417
12.5%
2 16192
 
11.0%
4 12867
 
8.7%
3 12251
 
8.3%
5 11383
 
7.7%
9 9513
 
6.4%
8 8221
 
5.6%
7 7772
 
5.3%
6 7456
 
5.1%
Other Punctuation
ValueCountFrequency (%)
. 59040
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2007
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 208647
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 59040
28.3%
1 43528
20.9%
0 18417
 
8.8%
2 16192
 
7.8%
4 12867
 
6.2%
3 12251
 
5.9%
5 11383
 
5.5%
9 9513
 
4.6%
8 8221
 
3.9%
7 7772
 
3.7%
Other values (2) 9463
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 208647
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 59040
28.3%
1 43528
20.9%
0 18417
 
8.8%
2 16192
 
7.8%
4 12867
 
6.2%
3 12251
 
5.9%
5 11383
 
5.5%
9 9513
 
4.6%
8 8221
 
3.9%
7 7772
 
3.7%
Other values (2) 9463
 
4.5%
Distinct181
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size236.0 KiB
2025-01-11T12:23:19.811487image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.2815926
Min length1

Characters and Unicode

Total characters68879
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row3.8
2nd row8
3rd row5.7
4th row6.1
5th row6.1
ValueCountFrequency (%)
99 3368
 
11.2%
10 953
 
3.2%
11 877
 
2.9%
12 875
 
2.9%
13 774
 
2.6%
15 693
 
2.3%
14 684
 
2.3%
16 615
 
2.0%
591
 
2.0%
17 578
 
1.9%
Other values (171) 20181
66.8%
2025-01-11T12:23:20.186715image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 10356
15.0%
1 10186
14.8%
. 8904
12.9%
2 7059
10.2%
3 6001
8.7%
4 5200
7.5%
5 4683
6.8%
6 4522
6.6%
7 4131
 
6.0%
8 3961
 
5.8%
Other values (2) 3876
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 58202
84.5%
Other Punctuation 8904
 
12.9%
Dash Punctuation 1773
 
2.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 10356
17.8%
1 10186
17.5%
2 7059
12.1%
3 6001
10.3%
4 5200
8.9%
5 4683
8.0%
6 4522
7.8%
7 4131
 
7.1%
8 3961
 
6.8%
0 2103
 
3.6%
Other Punctuation
ValueCountFrequency (%)
. 8904
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1773
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 68879
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
9 10356
15.0%
1 10186
14.8%
. 8904
12.9%
2 7059
10.2%
3 6001
8.7%
4 5200
7.5%
5 4683
6.8%
6 4522
6.6%
7 4131
 
6.0%
8 3961
 
5.8%
Other values (2) 3876
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 68879
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 10356
15.0%
1 10186
14.8%
. 8904
12.9%
2 7059
10.2%
3 6001
8.7%
4 5200
7.5%
5 4683
6.8%
6 4522
6.6%
7 4131
 
6.0%
8 3961
 
5.8%
Other values (2) 3876
 
5.6%

running_position_5
Real number (ℝ)

High correlation  Missing 

Distinct14
Distinct (%)0.4%
Missing26425
Missing (%)87.5%
Infinite0
Infinite (%)0.0%
Mean6.7646121
Minimum1
Maximum14
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size236.0 KiB
2025-01-11T12:23:20.297112image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median7
Q310
95-th percentile13
Maximum14
Range13
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.7159097
Coefficient of variation (CV)0.549316
Kurtosis-1.0822133
Mean6.7646121
Median Absolute Deviation (MAD)3
Skewness0.12514101
Sum25462
Variance13.807985
MonotonicityNot monotonic
2025-01-11T12:23:20.399621image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
2 307
 
1.0%
4 307
 
1.0%
1 306
 
1.0%
3 306
 
1.0%
5 306
 
1.0%
6 306
 
1.0%
8 302
 
1.0%
7 301
 
1.0%
9 296
 
1.0%
10 279
 
0.9%
Other values (4) 748
 
2.5%
(Missing) 26425
87.5%
ValueCountFrequency (%)
1 306
1.0%
2 307
1.0%
3 306
1.0%
4 307
1.0%
5 306
1.0%
6 306
1.0%
7 301
1.0%
8 302
1.0%
9 296
1.0%
10 279
0.9%
ValueCountFrequency (%)
14 106
 
0.4%
13 131
0.4%
12 245
0.8%
11 266
0.9%
10 279
0.9%
9 296
1.0%
8 302
1.0%
7 301
1.0%
6 306
1.0%
5 306
1.0%

running_position_6
Real number (ℝ)

High correlation  Missing 

Distinct14
Distinct (%)2.6%
Missing29640
Missing (%)98.2%
Infinite0
Infinite (%)0.0%
Mean6.3242259
Minimum1
Maximum14
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size236.0 KiB
2025-01-11T12:23:20.494845image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median6
Q39
95-th percentile12
Maximum14
Range13
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.4604881
Coefficient of variation (CV)0.54717971
Kurtosis-1.0808918
Mean6.3242259
Median Absolute Deviation (MAD)3
Skewness0.12668165
Sum3472
Variance11.974978
MonotonicityNot monotonic
2025-01-11T12:23:20.596181image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
1 49
 
0.2%
6 49
 
0.2%
4 48
 
0.2%
3 48
 
0.2%
5 48
 
0.2%
8 48
 
0.2%
2 47
 
0.2%
7 47
 
0.2%
9 42
 
0.1%
10 41
 
0.1%
Other values (4) 82
 
0.3%
(Missing) 29640
98.2%
ValueCountFrequency (%)
1 49
0.2%
2 47
0.2%
3 48
0.2%
4 48
0.2%
5 48
0.2%
6 49
0.2%
7 47
0.2%
8 48
0.2%
9 42
0.1%
10 41
0.1%
ValueCountFrequency (%)
14 3
 
< 0.1%
13 7
 
< 0.1%
12 33
0.1%
11 39
0.1%
10 41
0.1%
9 42
0.1%
8 48
0.2%
7 47
0.2%
6 49
0.2%
5 48
0.2%
Distinct2367
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Memory size236.0 KiB
2025-01-11T12:23:20.818301image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters241512
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2014-001
2nd row2014-001
3rd row2014-001
4th row2014-001
5th row2014-001
ValueCountFrequency (%)
2015-173 16
 
0.1%
2016-647 16
 
0.1%
2016-699 16
 
0.1%
2015-583 16
 
0.1%
2015-763 16
 
0.1%
2015-386 16
 
0.1%
2014-405 16
 
0.1%
2015-160 16
 
0.1%
2014-198 16
 
0.1%
2016-449 16
 
0.1%
Other values (2357) 30029
99.5%
2025-01-11T12:23:21.162498image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 40140
16.6%
1 40127
16.6%
0 40029
16.6%
- 30189
12.5%
6 20069
8.3%
5 19985
8.3%
4 19872
8.2%
3 9868
 
4.1%
7 9454
 
3.9%
8 5997
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 211323
87.5%
Dash Punctuation 30189
 
12.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 40140
19.0%
1 40127
19.0%
0 40029
18.9%
6 20069
9.5%
5 19985
9.5%
4 19872
9.4%
3 9868
 
4.7%
7 9454
 
4.5%
8 5997
 
2.8%
9 5782
 
2.7%
Dash Punctuation
ValueCountFrequency (%)
- 30189
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 241512
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 40140
16.6%
1 40127
16.6%
0 40029
16.6%
- 30189
12.5%
6 20069
8.3%
5 19985
8.3%
4 19872
8.2%
3 9868
 
4.1%
7 9454
 
3.9%
8 5997
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 241512
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 40140
16.6%
1 40127
16.6%
0 40029
16.6%
- 30189
12.5%
6 20069
8.3%
5 19985
8.3%
4 19872
8.2%
3 9868
 
4.1%
7 9454
 
3.9%
8 5997
 
2.5%

src
Text

Distinct2367
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Memory size236.0 KiB
2025-01-11T12:23:21.335291image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length16
Median length15
Mean length15.083209
Min length15

Characters and Unicode

Total characters455347
Distinct characters16
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20140914-1.html
2nd row20140914-1.html
3rd row20140914-1.html
4th row20140914-1.html
5th row20140914-1.html
ValueCountFrequency (%)
20151114-4.html 16
 
0.1%
20170513-5.html 16
 
0.1%
20170604-3.html 16
 
0.1%
20160424-1.html 16
 
0.1%
20160701-10.html 16
 
0.1%
20160206-10.html 16
 
0.1%
20150221-5.html 16
 
0.1%
20151108-11.html 16
 
0.1%
20141130-4.html 16
 
0.1%
20170226-6.html 16
 
0.1%
Other values (2357) 30029
99.5%
2025-01-11T12:23:21.622133image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 68917
15.1%
1 66271
14.6%
2 50766
11.1%
- 30189
6.6%
h 30189
6.6%
. 30189
6.6%
t 30189
6.6%
m 30189
6.6%
l 30189
6.6%
5 19226
 
4.2%
Other values (6) 69033
15.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 274213
60.2%
Lowercase Letter 120756
26.5%
Dash Punctuation 30189
 
6.6%
Other Punctuation 30189
 
6.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 68917
25.1%
1 66271
24.2%
2 50766
18.5%
5 19226
 
7.0%
6 19172
 
7.0%
7 14095
 
5.1%
4 12664
 
4.6%
3 9812
 
3.6%
9 7278
 
2.7%
8 6012
 
2.2%
Lowercase Letter
ValueCountFrequency (%)
h 30189
25.0%
t 30189
25.0%
m 30189
25.0%
l 30189
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 30189
100.0%
Other Punctuation
ValueCountFrequency (%)
. 30189
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 334591
73.5%
Latin 120756
 
26.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 68917
20.6%
1 66271
19.8%
2 50766
15.2%
- 30189
9.0%
. 30189
9.0%
5 19226
 
5.7%
6 19172
 
5.7%
7 14095
 
4.2%
4 12664
 
3.8%
3 9812
 
2.9%
Other values (2) 13290
 
4.0%
Latin
ValueCountFrequency (%)
h 30189
25.0%
t 30189
25.0%
m 30189
25.0%
l 30189
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 455347
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 68917
15.1%
1 66271
14.6%
2 50766
11.1%
- 30189
6.6%
h 30189
6.6%
. 30189
6.6%
t 30189
6.6%
m 30189
6.6%
l 30189
6.6%
5 19226
 
4.2%
Other values (6) 69033
15.2%
Distinct254
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size236.0 KiB
Minimum2014-09-14 00:00:00
Maximum2017-07-16 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2025-01-11T12:23:21.766273image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:21.895940image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

race_course
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size236.0 KiB
Sha Tin
19935 
Happy Valley
10254 

Length

Max length12
Median length7
Mean length8.6983007
Min length7

Characters and Unicode

Total characters262593
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSha Tin
2nd rowSha Tin
3rd rowSha Tin
4th rowSha Tin
5th rowSha Tin

Common Values

ValueCountFrequency (%)
Sha Tin 19935
66.0%
Happy Valley 10254
34.0%

Length

2025-01-11T12:23:22.010654image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-01-11T12:23:22.108325image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
ValueCountFrequency (%)
sha 19935
33.0%
tin 19935
33.0%
happy 10254
17.0%
valley 10254
17.0%

Most occurring characters

ValueCountFrequency (%)
a 40443
15.4%
30189
11.5%
l 20508
7.8%
y 20508
7.8%
p 20508
7.8%
T 19935
7.6%
h 19935
7.6%
S 19935
7.6%
i 19935
7.6%
n 19935
7.6%
Other values (3) 30762
11.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 172026
65.5%
Uppercase Letter 60378
 
23.0%
Space Separator 30189
 
11.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 40443
23.5%
l 20508
11.9%
y 20508
11.9%
p 20508
11.9%
h 19935
11.6%
i 19935
11.6%
n 19935
11.6%
e 10254
 
6.0%
Uppercase Letter
ValueCountFrequency (%)
T 19935
33.0%
S 19935
33.0%
H 10254
17.0%
V 10254
17.0%
Space Separator
ValueCountFrequency (%)
30189
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 232404
88.5%
Common 30189
 
11.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 40443
17.4%
l 20508
8.8%
y 20508
8.8%
p 20508
8.8%
T 19935
8.6%
h 19935
8.6%
S 19935
8.6%
i 19935
8.6%
n 19935
8.6%
H 10254
 
4.4%
Other values (2) 20508
8.8%
Common
ValueCountFrequency (%)
30189
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 262593
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 40443
15.4%
30189
11.5%
l 20508
7.8%
y 20508
7.8%
p 20508
7.8%
T 19935
7.6%
h 19935
7.6%
S 19935
7.6%
i 19935
7.6%
n 19935
7.6%
Other values (3) 30762
11.7%

race_number
Real number (ℝ)

Distinct11
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.284342
Minimum1
Maximum11
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size236.0 KiB
2025-01-11T12:23:22.195931image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median5
Q38
95-th percentile10
Maximum11
Range10
Interquartile range (IQR)5

Descriptive statistics

Standard deviation2.8159219
Coefficient of variation (CV)0.53288032
Kurtosis-1.0567953
Mean5.284342
Median Absolute Deviation (MAD)2
Skewness0.13105476
Sum159529
Variance7.9294159
MonotonicityNot monotonic
2025-01-11T12:23:22.304659image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
6 3276
10.9%
5 3270
10.8%
4 3244
10.7%
2 3237
10.7%
1 3157
10.5%
8 3144
10.4%
3 3134
10.4%
7 3120
10.3%
9 2095
6.9%
10 1965
6.5%
ValueCountFrequency (%)
1 3157
10.5%
2 3237
10.7%
3 3134
10.4%
4 3244
10.7%
5 3270
10.8%
6 3276
10.9%
7 3120
10.3%
8 3144
10.4%
9 2095
6.9%
10 1965
6.5%
ValueCountFrequency (%)
11 547
 
1.8%
10 1965
6.5%
9 2095
6.9%
8 3144
10.4%
7 3120
10.3%
6 3276
10.9%
5 3270
10.8%
4 3244
10.7%
3 3134
10.4%
2 3237
10.7%

race_class
Categorical

Distinct16
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size236.0 KiB
Class 4
11145 
Class 3
9746 
Class 5
4377 
Class 2
2855 
Class 1
 
532
Other values (11)
1534 

Length

Max length27
Median length7
Mean length7.422008
Min length7

Characters and Unicode

Total characters224063
Distinct characters33
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowClass 5
2nd rowClass 5
3rd rowClass 5
4th rowClass 5
5th rowClass 5

Common Values

ValueCountFrequency (%)
Class 4 11145
36.9%
Class 3 9746
32.3%
Class 5 4377
 
14.5%
Class 2 2855
 
9.5%
Class 1 532
 
1.8%
Group One 352
 
1.2%
Hong Kong Group Three 294
 
1.0%
Group Two 145
 
0.5%
Griffin Race 145
 
0.5%
Class 4 (Restricted) 117
 
0.4%
Other values (6) 481
 
1.6%

Length

2025-01-11T12:23:22.429541image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
class 28871
46.8%
4 11335
 
18.4%
3 9772
 
15.8%
5 4377
 
7.1%
2 2855
 
4.6%
group 1100
 
1.8%
1 532
 
0.9%
hong 492
 
0.8%
kong 492
 
0.8%
one 462
 
0.7%
Other values (7) 1389
 
2.3%

Most occurring characters

ValueCountFrequency (%)
s 57932
25.9%
31488
14.1%
a 29188
13.0%
C 28970
12.9%
l 28970
12.9%
4 11335
 
5.1%
3 9772
 
4.4%
5 4377
 
2.0%
2 2855
 
1.3%
o 2515
 
1.1%
Other values (23) 16661
 
7.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 130466
58.2%
Uppercase Letter 32806
 
14.6%
Space Separator 31488
 
14.1%
Decimal Number 28871
 
12.9%
Open Punctuation 216
 
0.1%
Close Punctuation 216
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 57932
44.4%
a 29188
22.4%
l 28970
22.2%
o 2515
 
1.9%
e 1969
 
1.5%
r 1840
 
1.4%
n 1789
 
1.4%
p 1199
 
0.9%
u 1100
 
0.8%
g 984
 
0.8%
Other values (7) 2980
 
2.3%
Uppercase Letter
ValueCountFrequency (%)
C 28970
88.3%
G 1245
 
3.8%
T 638
 
1.9%
H 492
 
1.5%
K 492
 
1.5%
O 462
 
1.4%
R 408
 
1.2%
S 99
 
0.3%
Decimal Number
ValueCountFrequency (%)
4 11335
39.3%
3 9772
33.8%
5 4377
 
15.2%
2 2855
 
9.9%
1 532
 
1.8%
Space Separator
ValueCountFrequency (%)
31488
100.0%
Open Punctuation
ValueCountFrequency (%)
( 216
100.0%
Close Punctuation
ValueCountFrequency (%)
) 216
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 163272
72.9%
Common 60791
 
27.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 57932
35.5%
a 29188
17.9%
C 28970
17.7%
l 28970
17.7%
o 2515
 
1.5%
e 1969
 
1.2%
r 1840
 
1.1%
n 1789
 
1.1%
G 1245
 
0.8%
p 1199
 
0.7%
Other values (15) 7655
 
4.7%
Common
ValueCountFrequency (%)
31488
51.8%
4 11335
 
18.6%
3 9772
 
16.1%
5 4377
 
7.2%
2 2855
 
4.7%
1 532
 
0.9%
( 216
 
0.4%
) 216
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 224063
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 57932
25.9%
31488
14.1%
a 29188
13.0%
C 28970
12.9%
l 28970
12.9%
4 11335
 
5.1%
3 9772
 
4.4%
5 4377
 
2.0%
2 2855
 
1.3%
o 2515
 
1.1%
Other values (23) 16661
 
7.4%

race_distance
Real number (ℝ)

Distinct9
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1414.8465
Minimum1000
Maximum2400
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size236.0 KiB
2025-01-11T12:23:22.543225image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1000
5-th percentile1000
Q11200
median1400
Q31650
95-th percentile1800
Maximum2400
Range1400
Interquartile range (IQR)450

Descriptive statistics

Standard deviation279.76782
Coefficient of variation (CV)0.19773723
Kurtosis-0.094362875
Mean1414.8465
Median Absolute Deviation (MAD)200
Skewness0.55782226
Sum42712800
Variance78270.035
MonotonicityNot monotonic
2025-01-11T12:23:22.642206image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1200 10158
33.6%
1400 5466
18.1%
1650 4844
16.0%
1000 3046
 
10.1%
1600 2843
 
9.4%
1800 2561
 
8.5%
2000 710
 
2.4%
2200 464
 
1.5%
2400 97
 
0.3%
ValueCountFrequency (%)
1000 3046
 
10.1%
1200 10158
33.6%
1400 5466
18.1%
1600 2843
 
9.4%
1650 4844
16.0%
1800 2561
 
8.5%
2000 710
 
2.4%
2200 464
 
1.5%
2400 97
 
0.3%
ValueCountFrequency (%)
2400 97
 
0.3%
2200 464
 
1.5%
2000 710
 
2.4%
1800 2561
 
8.5%
1650 4844
16.0%
1600 2843
 
9.4%
1400 5466
18.1%
1200 10158
33.6%
1000 3046
 
10.1%

track_condition
Categorical

Imbalance 

Distinct9
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size236.0 KiB
GOOD
16466 
GOOD TO FIRM
11059 
GOOD TO YIELDING
 
1578
YIELDING
 
360
WET SLOW
 
292
Other values (4)
 
434

Length

Max length16
Median length4
Mean length7.6716685
Min length4

Characters and Unicode

Total characters231600
Distinct characters16
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowGOOD TO FIRM
2nd rowGOOD TO FIRM
3rd rowGOOD TO FIRM
4th rowGOOD TO FIRM
5th rowGOOD TO FIRM

Common Values

ValueCountFrequency (%)
GOOD 16466
54.5%
GOOD TO FIRM 11059
36.6%
GOOD TO YIELDING 1578
 
5.2%
YIELDING 360
 
1.2%
WET SLOW 292
 
1.0%
FAST 239
 
0.8%
WET FAST 171
 
0.6%
YIELDING TO SOFT 12
 
< 0.1%
SOFT 12
 
< 0.1%

Length

2025-01-11T12:23:22.768588image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-01-11T12:23:22.904017image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
ValueCountFrequency (%)
good 29103
52.0%
to 12649
22.6%
firm 11059
 
19.8%
yielding 1950
 
3.5%
wet 463
 
0.8%
fast 410
 
0.7%
slow 292
 
0.5%
soft 24
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
O 71171
30.7%
G 31053
13.4%
D 31053
13.4%
25761
 
11.1%
I 14959
 
6.5%
T 13546
 
5.8%
F 11493
 
5.0%
R 11059
 
4.8%
M 11059
 
4.8%
E 2413
 
1.0%
Other values (6) 8033
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 205839
88.9%
Space Separator 25761
 
11.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
O 71171
34.6%
G 31053
15.1%
D 31053
15.1%
I 14959
 
7.3%
T 13546
 
6.6%
F 11493
 
5.6%
R 11059
 
5.4%
M 11059
 
5.4%
E 2413
 
1.2%
L 2242
 
1.1%
Other values (5) 5791
 
2.8%
Space Separator
ValueCountFrequency (%)
25761
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 205839
88.9%
Common 25761
 
11.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
O 71171
34.6%
G 31053
15.1%
D 31053
15.1%
I 14959
 
7.3%
T 13546
 
6.6%
F 11493
 
5.6%
R 11059
 
5.4%
M 11059
 
5.4%
E 2413
 
1.2%
L 2242
 
1.1%
Other values (5) 5791
 
2.8%
Common
ValueCountFrequency (%)
25761
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 231600
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
O 71171
30.7%
G 31053
13.4%
D 31053
13.4%
25761
 
11.1%
I 14959
 
6.5%
T 13546
 
5.8%
F 11493
 
5.0%
R 11059
 
4.8%
M 11059
 
4.8%
E 2413
 
1.0%
Other values (6) 8033
 
3.5%
Distinct1084
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size236.0 KiB
2025-01-11T12:23:23.399099image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length85
Median length68
Mean length23.305144
Min length12

Characters and Unicode

Total characters703559
Distinct characters51
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowTIM WA HANDICAP
2nd rowTIM WA HANDICAP
3rd rowTIM WA HANDICAP
4th rowTIM WA HANDICAP
5th rowTIM WA HANDICAP
ValueCountFrequency (%)
handicap 29376
28.2%
the 4681
 
4.5%
cup 2640
 
2.5%
kong 1215
 
1.2%
hong 1056
 
1.0%
club 920
 
0.9%
challenge 833
 
0.8%
trophy 727
 
0.7%
shan 700
 
0.7%
tin 666
 
0.6%
Other values (1186) 61387
58.9%
2025-01-11T12:23:23.926824image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 92200
13.1%
74012
10.5%
N 62673
 
8.9%
I 56486
 
8.0%
H 50253
 
7.1%
C 49088
 
7.0%
P 41094
 
5.8%
E 38117
 
5.4%
D 36803
 
5.2%
O 26175
 
3.7%
Other values (41) 176658
25.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 619689
88.1%
Space Separator 74012
 
10.5%
Close Punctuation 3556
 
0.5%
Open Punctuation 3556
 
0.5%
Other Punctuation 1494
 
0.2%
Decimal Number 752
 
0.1%
Dash Punctuation 387
 
0.1%
Lowercase Letter 113
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 92200
14.9%
N 62673
10.1%
I 56486
 
9.1%
H 50253
 
8.1%
C 49088
 
7.9%
P 41094
 
6.6%
E 38117
 
6.2%
D 36803
 
5.9%
O 26175
 
4.2%
T 23739
 
3.8%
Other values (16) 143061
23.1%
Decimal Number
ValueCountFrequency (%)
1 200
26.6%
0 106
14.1%
4 105
14.0%
2 90
12.0%
3 78
 
10.4%
5 66
 
8.8%
8 39
 
5.2%
7 28
 
3.7%
9 26
 
3.5%
6 14
 
1.9%
Other Punctuation
ValueCountFrequency (%)
' 867
58.0%
& 324
 
21.7%
. 264
 
17.7%
@ 14
 
0.9%
: 14
 
0.9%
, 11
 
0.7%
Lowercase Letter
ValueCountFrequency (%)
i 43
38.1%
n 28
24.8%
a 14
 
12.4%
e 14
 
12.4%
o 14
 
12.4%
Space Separator
ValueCountFrequency (%)
74012
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3556
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3556
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 387
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 619802
88.1%
Common 83757
 
11.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 92200
14.9%
N 62673
10.1%
I 56486
 
9.1%
H 50253
 
8.1%
C 49088
 
7.9%
P 41094
 
6.6%
E 38117
 
6.1%
D 36803
 
5.9%
O 26175
 
4.2%
T 23739
 
3.8%
Other values (21) 143174
23.1%
Common
ValueCountFrequency (%)
74012
88.4%
) 3556
 
4.2%
( 3556
 
4.2%
' 867
 
1.0%
- 387
 
0.5%
& 324
 
0.4%
. 264
 
0.3%
1 200
 
0.2%
0 106
 
0.1%
4 105
 
0.1%
Other values (10) 380
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 703559
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 92200
13.1%
74012
10.5%
N 62673
 
8.9%
I 56486
 
8.0%
H 50253
 
7.1%
C 49088
 
7.0%
P 41094
 
5.8%
E 38117
 
5.4%
D 36803
 
5.2%
O 26175
 
3.7%
Other values (41) 176658
25.1%

track
Categorical

High correlation 

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size236.0 KiB
TURF - "A" COURSE
6630 
TURF - "C" COURSE
5596 
TURF - "C+3" COURSE
5140 
TURF - "B" COURSE
3721 
ALL WEATHER TRACK
3648 
Other values (2)
5454 

Length

Max length19
Median length17
Mean length17.701845
Min length17

Characters and Unicode

Total characters534401
Distinct characters20
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowTURF - "A" COURSE
2nd rowTURF - "A" COURSE
3rd rowTURF - "A" COURSE
4th rowTURF - "A" COURSE
5th rowTURF - "A" COURSE

Common Values

ValueCountFrequency (%)
TURF - "A" COURSE 6630
22.0%
TURF - "C" COURSE 5596
18.5%
TURF - "C+3" COURSE 5140
17.0%
TURF - "B" COURSE 3721
12.3%
ALL WEATHER TRACK 3648
12.1%
TURF - "B+2" COURSE 2765
9.2%
TURF - "A+3" COURSE 2689
8.9%

Length

2025-01-11T12:23:24.069239image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-01-11T12:23:24.206937image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
ValueCountFrequency (%)
turf 26541
22.7%
26541
22.7%
course 26541
22.7%
a 6630
 
5.7%
c 5596
 
4.8%
c+3 5140
 
4.4%
b 3721
 
3.2%
all 3648
 
3.1%
weather 3648
 
3.1%
track 3648
 
3.1%
Other values (2) 5454
 
4.7%

Most occurring characters

ValueCountFrequency (%)
86919
16.3%
R 60378
11.3%
" 53082
9.9%
U 53082
9.9%
C 40925
7.7%
T 33837
 
6.3%
E 33837
 
6.3%
F 26541
 
5.0%
O 26541
 
5.0%
- 26541
 
5.0%
Other values (10) 92718
17.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 346671
64.9%
Space Separator 86919
 
16.3%
Other Punctuation 53082
 
9.9%
Dash Punctuation 26541
 
5.0%
Math Symbol 10594
 
2.0%
Decimal Number 10594
 
2.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
R 60378
17.4%
U 53082
15.3%
C 40925
11.8%
T 33837
9.8%
E 33837
9.8%
F 26541
7.7%
O 26541
7.7%
S 26541
7.7%
A 20263
 
5.8%
L 7296
 
2.1%
Other values (4) 17430
 
5.0%
Decimal Number
ValueCountFrequency (%)
3 7829
73.9%
2 2765
 
26.1%
Space Separator
ValueCountFrequency (%)
86919
100.0%
Other Punctuation
ValueCountFrequency (%)
" 53082
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 26541
100.0%
Math Symbol
ValueCountFrequency (%)
+ 10594
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 346671
64.9%
Common 187730
35.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
R 60378
17.4%
U 53082
15.3%
C 40925
11.8%
T 33837
9.8%
E 33837
9.8%
F 26541
7.7%
O 26541
7.7%
S 26541
7.7%
A 20263
 
5.8%
L 7296
 
2.1%
Other values (4) 17430
 
5.0%
Common
ValueCountFrequency (%)
86919
46.3%
" 53082
28.3%
- 26541
 
14.1%
+ 10594
 
5.6%
3 7829
 
4.2%
2 2765
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 534401
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
86919
16.3%
R 60378
11.3%
" 53082
9.9%
U 53082
9.9%
C 40925
7.7%
T 33837
 
6.3%
E 33837
 
6.3%
F 26541
 
5.0%
O 26541
 
5.0%
- 26541
 
5.0%
Other values (10) 92718
17.3%
Distinct2367
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Memory size236.0 KiB
2025-01-11T12:23:24.641425image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length35
Median length29
Mean length21.248832
Min length17

Characters and Unicode

Total characters641481
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row13.59 22.08 23.11 23.55
2nd row13.59 22.08 23.11 23.55
3rd row13.59 22.08 23.11 23.55
4th row13.59 22.08 23.11 23.55
5th row13.59 22.08 23.11 23.55
ValueCountFrequency (%)
23.53 801
 
0.7%
23.20 661
 
0.6%
23.70 657
 
0.6%
23.88 654
 
0.6%
23.81 633
 
0.6%
23.92 616
 
0.6%
23.62 610
 
0.5%
23.45 599
 
0.5%
23.32 593
 
0.5%
23.40 592
 
0.5%
Other values (878) 105529
94.3%
2025-01-11T12:23:25.079090image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 145418
22.7%
. 111945
17.5%
81756
12.7%
3 71242
11.1%
4 44848
 
7.0%
1 38274
 
6.0%
5 29221
 
4.6%
7 25855
 
4.0%
8 25016
 
3.9%
6 23244
 
3.6%
Other values (2) 44662
 
7.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 447780
69.8%
Other Punctuation 111945
 
17.5%
Space Separator 81756
 
12.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 145418
32.5%
3 71242
15.9%
4 44848
 
10.0%
1 38274
 
8.5%
5 29221
 
6.5%
7 25855
 
5.8%
8 25016
 
5.6%
6 23244
 
5.2%
0 22581
 
5.0%
9 22081
 
4.9%
Other Punctuation
ValueCountFrequency (%)
. 111945
100.0%
Space Separator
ValueCountFrequency (%)
81756
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 641481
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 145418
22.7%
. 111945
17.5%
81756
12.7%
3 71242
11.1%
4 44848
 
7.0%
1 38274
 
6.0%
5 29221
 
4.6%
7 25855
 
4.0%
8 25016
 
3.9%
6 23244
 
3.6%
Other values (2) 44662
 
7.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 641481
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 145418
22.7%
. 111945
17.5%
81756
12.7%
3 71242
11.1%
4 44848
 
7.0%
1 38274
 
6.0%
5 29221
 
4.6%
7 25855
 
4.0%
8 25016
 
3.9%
6 23244
 
3.6%
Other values (2) 44662
 
7.0%
Distinct2367
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Memory size236.0 KiB
2025-01-11T12:23:25.358631image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8275
Median length2930
Mean length2440.0479
Min length92

Characters and Unicode

Total characters73662605
Distinct characters95
Distinct categories13 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row When about to enter the track, SHANTARAAM became fractious, reared on two occasions and then threw itself down. SHANTARAAM was examined by Veterinary Officer who said in his opinion it was unsuitable to race. Accordingly, SHANTARAAM was withdrawn by order of the Stewards acting on veterinary advice. Before being allowed to race again, SHANTARAAM will be subjected to an official veterinary examination. In this incident, O Doleuze was dislodged from SHANTARAAM. O Doleuze was subsequently examined by the Club’s medical officers and cleared to fulfil his remaining race riding engagements. SUPREME PROFIT began only fairly. Approaching the 1300 Metres, TAI PO FORTUNE blundered when being shifted in behind AMAZING GIFT. TAI PO FORTUNE then got its head up when racing keenly passing the 1000 Metres. Near the 800 Metres, COOL PAL was left racing wide and without cover. Passing the 300 Metres, SUPREME PROFIT lay in and proved reluctant to shift to the outside of DOUBLE DRAGON. SUPREME PROFIT continued to hang in under pressure and over the concluding stages raced tight outside GOLDWEAVER. Because of this, SUPREME PROFIT was not able to be properly tested over the concluding stages. DOUBLE DRAGON and PLAIN BLUE BANNER were sent for sampling.
2nd row When about to enter the track, SHANTARAAM became fractious, reared on two occasions and then threw itself down. SHANTARAAM was examined by Veterinary Officer who said in his opinion it was unsuitable to race. Accordingly, SHANTARAAM was withdrawn by order of the Stewards acting on veterinary advice. Before being allowed to race again, SHANTARAAM will be subjected to an official veterinary examination. In this incident, O Doleuze was dislodged from SHANTARAAM. O Doleuze was subsequently examined by the Club’s medical officers and cleared to fulfil his remaining race riding engagements. SUPREME PROFIT began only fairly. Approaching the 1300 Metres, TAI PO FORTUNE blundered when being shifted in behind AMAZING GIFT. TAI PO FORTUNE then got its head up when racing keenly passing the 1000 Metres. Near the 800 Metres, COOL PAL was left racing wide and without cover. Passing the 300 Metres, SUPREME PROFIT lay in and proved reluctant to shift to the outside of DOUBLE DRAGON. SUPREME PROFIT continued to hang in under pressure and over the concluding stages raced tight outside GOLDWEAVER. Because of this, SUPREME PROFIT was not able to be properly tested over the concluding stages. DOUBLE DRAGON and PLAIN BLUE BANNER were sent for sampling.
3rd row When about to enter the track, SHANTARAAM became fractious, reared on two occasions and then threw itself down. SHANTARAAM was examined by Veterinary Officer who said in his opinion it was unsuitable to race. Accordingly, SHANTARAAM was withdrawn by order of the Stewards acting on veterinary advice. Before being allowed to race again, SHANTARAAM will be subjected to an official veterinary examination. In this incident, O Doleuze was dislodged from SHANTARAAM. O Doleuze was subsequently examined by the Club’s medical officers and cleared to fulfil his remaining race riding engagements. SUPREME PROFIT began only fairly. Approaching the 1300 Metres, TAI PO FORTUNE blundered when being shifted in behind AMAZING GIFT. TAI PO FORTUNE then got its head up when racing keenly passing the 1000 Metres. Near the 800 Metres, COOL PAL was left racing wide and without cover. Passing the 300 Metres, SUPREME PROFIT lay in and proved reluctant to shift to the outside of DOUBLE DRAGON. SUPREME PROFIT continued to hang in under pressure and over the concluding stages raced tight outside GOLDWEAVER. Because of this, SUPREME PROFIT was not able to be properly tested over the concluding stages. DOUBLE DRAGON and PLAIN BLUE BANNER were sent for sampling.
4th row When about to enter the track, SHANTARAAM became fractious, reared on two occasions and then threw itself down. SHANTARAAM was examined by Veterinary Officer who said in his opinion it was unsuitable to race. Accordingly, SHANTARAAM was withdrawn by order of the Stewards acting on veterinary advice. Before being allowed to race again, SHANTARAAM will be subjected to an official veterinary examination. In this incident, O Doleuze was dislodged from SHANTARAAM. O Doleuze was subsequently examined by the Club’s medical officers and cleared to fulfil his remaining race riding engagements. SUPREME PROFIT began only fairly. Approaching the 1300 Metres, TAI PO FORTUNE blundered when being shifted in behind AMAZING GIFT. TAI PO FORTUNE then got its head up when racing keenly passing the 1000 Metres. Near the 800 Metres, COOL PAL was left racing wide and without cover. Passing the 300 Metres, SUPREME PROFIT lay in and proved reluctant to shift to the outside of DOUBLE DRAGON. SUPREME PROFIT continued to hang in under pressure and over the concluding stages raced tight outside GOLDWEAVER. Because of this, SUPREME PROFIT was not able to be properly tested over the concluding stages. DOUBLE DRAGON and PLAIN BLUE BANNER were sent for sampling.
5th row When about to enter the track, SHANTARAAM became fractious, reared on two occasions and then threw itself down. SHANTARAAM was examined by Veterinary Officer who said in his opinion it was unsuitable to race. Accordingly, SHANTARAAM was withdrawn by order of the Stewards acting on veterinary advice. Before being allowed to race again, SHANTARAAM will be subjected to an official veterinary examination. In this incident, O Doleuze was dislodged from SHANTARAAM. O Doleuze was subsequently examined by the Club’s medical officers and cleared to fulfil his remaining race riding engagements. SUPREME PROFIT began only fairly. Approaching the 1300 Metres, TAI PO FORTUNE blundered when being shifted in behind AMAZING GIFT. TAI PO FORTUNE then got its head up when racing keenly passing the 1000 Metres. Near the 800 Metres, COOL PAL was left racing wide and without cover. Passing the 300 Metres, SUPREME PROFIT lay in and proved reluctant to shift to the outside of DOUBLE DRAGON. SUPREME PROFIT continued to hang in under pressure and over the concluding stages raced tight outside GOLDWEAVER. Because of this, SUPREME PROFIT was not able to be properly tested over the concluding stages. DOUBLE DRAGON and PLAIN BLUE BANNER were sent for sampling.
ValueCountFrequency (%)
the 844271
 
6.9%
to 428030
 
3.5%
and 358148
 
2.9%
was 329438
 
2.7%
of 294370
 
2.4%
in 281582
 
2.3%
metres 166333
 
1.4%
race 152915
 
1.2%
he 145549
 
1.2%
a 144633
 
1.2%
Other values (5699) 9093403
74.3%
2025-01-11T12:23:25.779453image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12575271
17.1%
e 6162101
 
8.4%
t 4492710
 
6.1%
a 3876758
 
5.3%
i 3718502
 
5.0%
n 3552820
 
4.8%
r 3164033
 
4.3%
o 3087976
 
4.2%
s 2827838
 
3.8%
h 2555332
 
3.5%
Other values (85) 27649264
37.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 47168496
64.0%
Space Separator 12575805
 
17.1%
Uppercase Letter 11548259
 
15.7%
Other Punctuation 1135859
 
1.5%
Decimal Number 673844
 
0.9%
Control 445902
 
0.6%
Open Punctuation 44683
 
0.1%
Close Punctuation 44683
 
0.1%
Dash Punctuation 12445
 
< 0.1%
Math Symbol 8156
 
< 0.1%
Other values (3) 4473
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 6162101
13.1%
t 4492710
 
9.5%
a 3876758
 
8.2%
i 3718502
 
7.9%
n 3552820
 
7.5%
r 3164033
 
6.7%
o 3087976
 
6.5%
s 2827838
 
6.0%
h 2555332
 
5.4%
d 2466127
 
5.2%
Other values (18) 11264299
23.9%
Uppercase Letter
ValueCountFrequency (%)
E 1099912
 
9.5%
A 1025583
 
8.9%
R 858075
 
7.4%
N 803372
 
7.0%
I 786297
 
6.8%
O 772705
 
6.7%
T 684159
 
5.9%
S 662901
 
5.7%
L 586612
 
5.1%
M 528631
 
4.6%
Other values (17) 3740012
32.4%
Decimal Number
ValueCountFrequency (%)
0 344182
51.1%
1 105977
 
15.7%
2 53946
 
8.0%
5 51847
 
7.7%
3 25805
 
3.8%
6 22771
 
3.4%
4 18650
 
2.8%
7 18553
 
2.8%
9 17709
 
2.6%
8 14404
 
2.1%
Other Punctuation
ValueCountFrequency (%)
. 581725
51.2%
, 523581
46.1%
' 18051
 
1.6%
/ 9201
 
0.8%
¿ 1318
 
0.1%
" 1303
 
0.1%
? 322
 
< 0.1%
; 298
 
< 0.1%
: 60
 
< 0.1%
Control
ValueCountFrequency (%)
392037
87.9%
€ 26817
 
6.0%
™ 24311
 
5.5%
 1176
 
0.3%
œ 961
 
0.2%
˜ 255
 
0.1%
231
 
0.1%
“ 114
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
> 4052
49.7%
< 4052
49.7%
+ 52
 
0.6%
Space Separator
ValueCountFrequency (%)
12575271
> 99.9%
  534
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 41666
93.2%
[ 3017
 
6.8%
Close Punctuation
ValueCountFrequency (%)
) 41666
93.2%
] 3017
 
6.8%
Dash Punctuation
ValueCountFrequency (%)
- 12445
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 3101
100.0%
Other Number
ValueCountFrequency (%)
½ 1344
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 28
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 58716755
79.7%
Common 14945850
 
20.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 6162101
 
10.5%
t 4492710
 
7.7%
a 3876758
 
6.6%
i 3718502
 
6.3%
n 3552820
 
6.1%
r 3164033
 
5.4%
o 3087976
 
5.3%
s 2827838
 
4.8%
h 2555332
 
4.4%
d 2466127
 
4.2%
Other values (45) 22812558
38.9%
Common
ValueCountFrequency (%)
12575271
84.1%
. 581725
 
3.9%
, 523581
 
3.5%
392037
 
2.6%
0 344182
 
2.3%
1 105977
 
0.7%
2 53946
 
0.4%
5 51847
 
0.3%
( 41666
 
0.3%
) 41666
 
0.3%
Other values (30) 233952
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 73577614
99.9%
None 84991
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12575271
17.1%
e 6162101
 
8.4%
t 4492710
 
6.1%
a 3876758
 
5.3%
i 3718502
 
5.1%
n 3552820
 
4.8%
r 3164033
 
4.3%
o 3087976
 
4.2%
s 2827838
 
3.8%
h 2555332
 
3.5%
Other values (73) 27564273
37.5%
None
ValueCountFrequency (%)
â 26817
31.6%
€ 26817
31.6%
™ 24311
28.6%
½ 1344
 
1.6%
¿ 1318
 
1.6%
ï 1318
 
1.6%
 1176
 
1.4%
œ 961
 
1.1%
  534
 
0.6%
˜ 255
 
0.3%
Other values (2) 140
 
0.2%

Season
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size236.0 KiB
Spring
9141 
Winter
8573 
Autumn
8220 
Summer
4255 

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters181134
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAutumn
2nd rowAutumn
3rd rowAutumn
4th rowAutumn
5th rowAutumn

Common Values

ValueCountFrequency (%)
Spring 9141
30.3%
Winter 8573
28.4%
Autumn 8220
27.2%
Summer 4255
14.1%

Length

2025-01-11T12:23:25.915068image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-01-11T12:23:26.014907image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
ValueCountFrequency (%)
spring 9141
30.3%
winter 8573
28.4%
autumn 8220
27.2%
summer 4255
14.1%

Most occurring characters

ValueCountFrequency (%)
n 25934
14.3%
r 21969
12.1%
u 20695
11.4%
i 17714
9.8%
t 16793
9.3%
m 16730
9.2%
S 13396
7.4%
e 12828
7.1%
p 9141
 
5.0%
g 9141
 
5.0%
Other values (2) 16793
9.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 150945
83.3%
Uppercase Letter 30189
 
16.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 25934
17.2%
r 21969
14.6%
u 20695
13.7%
i 17714
11.7%
t 16793
11.1%
m 16730
11.1%
e 12828
8.5%
p 9141
 
6.1%
g 9141
 
6.1%
Uppercase Letter
ValueCountFrequency (%)
S 13396
44.4%
W 8573
28.4%
A 8220
27.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 181134
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 25934
14.3%
r 21969
12.1%
u 20695
11.4%
i 17714
9.8%
t 16793
9.3%
m 16730
9.2%
S 13396
7.4%
e 12828
7.1%
p 9141
 
5.0%
g 9141
 
5.0%
Other values (2) 16793
9.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 181134
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 25934
14.3%
r 21969
12.1%
u 20695
11.4%
i 17714
9.8%
t 16793
9.3%
m 16730
9.2%
S 13396
7.4%
e 12828
7.1%
p 9141
 
5.0%
g 9141
 
5.0%
Other values (2) 16793
9.3%

Interactions

2025-01-11T12:23:12.229671image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:05.509947image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:06.335903image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:07.170039image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:08.000003image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:08.821790image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:09.631318image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:10.441838image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:11.366752image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:12.323273image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:05.605905image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:06.428764image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:07.262023image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:08.090987image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:08.912165image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:09.721525image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:10.530510image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:11.482605image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:12.421565image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:05.698560image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:06.522247image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:07.353341image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:08.184421image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:09.004508image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:09.814069image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:10.617765image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:11.573983image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:12.517545image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:05.792862image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:06.615418image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:07.446493image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:08.278129image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:09.094294image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:09.903867image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:10.705440image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:11.673060image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:12.612726image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:05.883040image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:06.706457image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:07.539368image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:08.369846image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:09.185083image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:09.995314image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:10.792616image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:11.762118image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:12.702557image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:05.973981image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:06.803926image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:07.629821image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:08.457962image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:09.275068image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:10.087842image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:10.884200image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:11.877059image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:12.796519image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:06.062992image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:06.893331image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:07.722620image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:08.549147image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:09.367870image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:10.177683image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:11.086467image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:11.965409image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:12.890626image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:06.153346image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:06.983073image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:07.817356image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:08.637597image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:09.454648image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:10.263326image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:11.173433image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:12.056704image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:12.979806image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:06.239540image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:07.069515image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:07.902439image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:08.723500image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:09.542349image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:10.349151image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:11.268638image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-01-11T12:23:12.136800image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Correlations

2025-01-11T12:23:26.124564image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Seasonactual_weightdrawfinishing_positionhorse_numberrace_classrace_courserace_distancerace_numberrunning_position_1running_position_2running_position_3running_position_4running_position_5running_position_6tracktrack_condition
Season1.0000.0590.0000.0000.0000.1300.0210.0590.0200.0000.0000.0000.0000.0000.0000.0750.168
actual_weight0.0591.0000.0110.0200.3660.1430.0530.0620.0490.0270.0330.0300.0360.0200.0970.0410.007
draw0.0000.0111.0000.2610.0280.0000.1870.0470.0210.1360.1360.0960.0610.0530.0620.0390.000
finishing_position0.0000.0200.2611.0000.0470.0300.1830.0520.0320.0890.1150.4650.7860.8670.9930.0410.000
horse_number0.0000.3660.0280.0471.0000.0000.1910.0080.0230.0790.0820.0970.1120.0990.1160.0420.000
race_class0.1300.1430.0000.0300.0001.0000.1860.1950.3390.0000.0000.0000.0000.0000.0000.1230.051
race_course0.0210.0530.1870.1830.1910.1861.0000.3810.2530.1850.1850.1850.1860.1880.1400.5270.161
race_distance0.0590.0620.0470.0520.0080.1950.3811.0000.0750.0080.0080.008-0.059-0.038-0.0390.1590.084
race_number0.0200.0490.0210.0320.0230.3390.2530.0751.0000.0230.0230.0230.0240.0150.0000.0710.051
running_position_10.0000.0270.1360.0890.0790.0000.1850.0080.0231.0000.9320.6340.2960.147-0.0240.0400.000
running_position_20.0000.0330.1360.1150.0820.0000.1850.0080.0230.9321.0000.7200.3240.148-0.0420.0410.000
running_position_30.0000.0300.0960.4650.0970.0000.1850.0080.0230.6340.7201.0000.4420.172-0.0440.0400.000
running_position_40.0000.0360.0610.7860.1120.0000.186-0.0590.0240.2960.3240.4421.0000.3380.0260.0310.000
running_position_50.0000.0200.0530.8670.0990.0000.188-0.0380.0150.1470.1480.1720.3381.0000.2980.0120.000
running_position_60.0000.0970.0620.9930.1160.0000.140-0.0390.000-0.024-0.042-0.0440.0260.2981.0000.0000.000
track0.0750.0410.0390.0410.0420.1230.5270.1590.0710.0400.0410.0400.0310.0120.0001.0000.226
track_condition0.1680.0070.0000.0000.0000.0510.1610.0840.0510.0000.0000.0000.0000.0000.0000.2261.000

Missing values

2025-01-11T12:23:13.170927image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
A simple visualization of nullity by column.
2025-01-11T12:23:13.632788image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2025-01-11T12:23:13.929157image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

finishing_positionhorse_numberhorse_namehorse_idjockeytraineractual_weightdeclared_horse_weightdrawlength_behind_winnerrunning_position_1running_position_2running_position_3running_position_4finish_timewin_oddsrunning_position_5running_position_6race_idsrcrace_daterace_courserace_numberrace_classrace_distancetrack_conditionrace_nametracksectional_timeincident_reportSeason
011.0DOUBLE DRAGONK019B PrebbleD Cruz13310321-1.02.02.01.01.22.333.8NaNNaN2014-00120140914-1.html2014-09-14Sha Tin1Class 51400GOOD TO FIRMTIM WA HANDICAPTURF - "A" COURSE13.59 22.08 23.11 23.55\n When about to enter the track, SHANTARAAM became fractious, reared on two occasions and then threw itself down. SHANTARAAM was examined by Veterinary Officer who said in his opinion it was unsuitable to race. Accordingly, SHANTARAAM was withdrawn by order of the Stewards acting on veterinary advice. Before being allowed to race again, SHANTARAAM will be subjected to an official veterinary examination. In this incident, O Doleuze was dislodged from SHANTARAAM. O Doleuze was subsequently examined by the Club’s medical officers and cleared to fulfil his remaining race riding engagements.\nSUPREME PROFIT began only fairly.\nApproaching the 1300 Metres, TAI PO FORTUNE blundered when being shifted in behind AMAZING GIFT. TAI PO FORTUNE then got its head up when racing keenly passing the 1000 Metres.\nNear the 800 Metres, COOL PAL was left racing wide and without cover.\nPassing the 300 Metres, SUPREME PROFIT lay in and proved reluctant to shift to the outside of DOUBLE DRAGON. SUPREME PROFIT continued to hang in under pressure and over the concluding stages raced tight outside GOLDWEAVER. Because of this, SUPREME PROFIT was not able to be properly tested over the concluding stages.\nDOUBLE DRAGON and PLAIN BLUE BANNER were sent for sampling.\nAutumn
122.0PLAIN BLUE BANNERS070D WhyteD E Ferraris13310751328.09.09.02.01.22.658NaNNaN2014-00120140914-1.html2014-09-14Sha Tin1Class 51400GOOD TO FIRMTIM WA HANDICAPTURF - "A" COURSE13.59 22.08 23.11 23.55\n When about to enter the track, SHANTARAAM became fractious, reared on two occasions and then threw itself down. SHANTARAAM was examined by Veterinary Officer who said in his opinion it was unsuitable to race. Accordingly, SHANTARAAM was withdrawn by order of the Stewards acting on veterinary advice. Before being allowed to race again, SHANTARAAM will be subjected to an official veterinary examination. In this incident, O Doleuze was dislodged from SHANTARAAM. O Doleuze was subsequently examined by the Club’s medical officers and cleared to fulfil his remaining race riding engagements.\nSUPREME PROFIT began only fairly.\nApproaching the 1300 Metres, TAI PO FORTUNE blundered when being shifted in behind AMAZING GIFT. TAI PO FORTUNE then got its head up when racing keenly passing the 1000 Metres.\nNear the 800 Metres, COOL PAL was left racing wide and without cover.\nPassing the 300 Metres, SUPREME PROFIT lay in and proved reluctant to shift to the outside of DOUBLE DRAGON. SUPREME PROFIT continued to hang in under pressure and over the concluding stages raced tight outside GOLDWEAVER. Because of this, SUPREME PROFIT was not able to be properly tested over the concluding stages.\nDOUBLE DRAGON and PLAIN BLUE BANNER were sent for sampling.\nAutumn
2310.0GOLDWEAVERP072Y T ChengY S Tsui1211065322.01.01.03.01.22.665.7NaNNaN2014-00120140914-1.html2014-09-14Sha Tin1Class 51400GOOD TO FIRMTIM WA HANDICAPTURF - "A" COURSE13.59 22.08 23.11 23.55\n When about to enter the track, SHANTARAAM became fractious, reared on two occasions and then threw itself down. SHANTARAAM was examined by Veterinary Officer who said in his opinion it was unsuitable to race. Accordingly, SHANTARAAM was withdrawn by order of the Stewards acting on veterinary advice. Before being allowed to race again, SHANTARAAM will be subjected to an official veterinary examination. In this incident, O Doleuze was dislodged from SHANTARAAM. O Doleuze was subsequently examined by the Club’s medical officers and cleared to fulfil his remaining race riding engagements.\nSUPREME PROFIT began only fairly.\nApproaching the 1300 Metres, TAI PO FORTUNE blundered when being shifted in behind AMAZING GIFT. TAI PO FORTUNE then got its head up when racing keenly passing the 1000 Metres.\nNear the 800 Metres, COOL PAL was left racing wide and without cover.\nPassing the 300 Metres, SUPREME PROFIT lay in and proved reluctant to shift to the outside of DOUBLE DRAGON. SUPREME PROFIT continued to hang in under pressure and over the concluding stages raced tight outside GOLDWEAVER. Because of this, SUPREME PROFIT was not able to be properly tested over the concluding stages.\nDOUBLE DRAGON and PLAIN BLUE BANNER were sent for sampling.\nAutumn
343.0SUPREME PROFITP230J MoreiraC S Shum1321222226.04.05.04.01.22.666.1NaNNaN2014-00120140914-1.html2014-09-14Sha Tin1Class 51400GOOD TO FIRMTIM WA HANDICAPTURF - "A" COURSE13.59 22.08 23.11 23.55\n When about to enter the track, SHANTARAAM became fractious, reared on two occasions and then threw itself down. SHANTARAAM was examined by Veterinary Officer who said in his opinion it was unsuitable to race. Accordingly, SHANTARAAM was withdrawn by order of the Stewards acting on veterinary advice. Before being allowed to race again, SHANTARAAM will be subjected to an official veterinary examination. In this incident, O Doleuze was dislodged from SHANTARAAM. O Doleuze was subsequently examined by the Club’s medical officers and cleared to fulfil his remaining race riding engagements.\nSUPREME PROFIT began only fairly.\nApproaching the 1300 Metres, TAI PO FORTUNE blundered when being shifted in behind AMAZING GIFT. TAI PO FORTUNE then got its head up when racing keenly passing the 1000 Metres.\nNear the 800 Metres, COOL PAL was left racing wide and without cover.\nPassing the 300 Metres, SUPREME PROFIT lay in and proved reluctant to shift to the outside of DOUBLE DRAGON. SUPREME PROFIT continued to hang in under pressure and over the concluding stages raced tight outside GOLDWEAVER. Because of this, SUPREME PROFIT was not able to be properly tested over the concluding stages.\nDOUBLE DRAGON and PLAIN BLUE BANNER were sent for sampling.\nAutumn
457.0THE ONLY KIDH173Z PurtonK W Lui125113694-1/49.010.010.05.01.23.026.1NaNNaN2014-00120140914-1.html2014-09-14Sha Tin1Class 51400GOOD TO FIRMTIM WA HANDICAPTURF - "A" COURSE13.59 22.08 23.11 23.55\n When about to enter the track, SHANTARAAM became fractious, reared on two occasions and then threw itself down. SHANTARAAM was examined by Veterinary Officer who said in his opinion it was unsuitable to race. Accordingly, SHANTARAAM was withdrawn by order of the Stewards acting on veterinary advice. Before being allowed to race again, SHANTARAAM will be subjected to an official veterinary examination. In this incident, O Doleuze was dislodged from SHANTARAAM. O Doleuze was subsequently examined by the Club’s medical officers and cleared to fulfil his remaining race riding engagements.\nSUPREME PROFIT began only fairly.\nApproaching the 1300 Metres, TAI PO FORTUNE blundered when being shifted in behind AMAZING GIFT. TAI PO FORTUNE then got its head up when racing keenly passing the 1000 Metres.\nNear the 800 Metres, COOL PAL was left racing wide and without cover.\nPassing the 300 Metres, SUPREME PROFIT lay in and proved reluctant to shift to the outside of DOUBLE DRAGON. SUPREME PROFIT continued to hang in under pressure and over the concluding stages raced tight outside GOLDWEAVER. Because of this, SUPREME PROFIT was not able to be properly tested over the concluding stages.\nDOUBLE DRAGON and PLAIN BLUE BANNER were sent for sampling.\nAutumn
569.0WINNING ADVANTAGEN359A SuboricsA T Millard1231100115-1/212.013.013.06.01.23.2024NaNNaN2014-00120140914-1.html2014-09-14Sha Tin1Class 51400GOOD TO FIRMTIM WA HANDICAPTURF - "A" COURSE13.59 22.08 23.11 23.55\n When about to enter the track, SHANTARAAM became fractious, reared on two occasions and then threw itself down. SHANTARAAM was examined by Veterinary Officer who said in his opinion it was unsuitable to race. Accordingly, SHANTARAAM was withdrawn by order of the Stewards acting on veterinary advice. Before being allowed to race again, SHANTARAAM will be subjected to an official veterinary examination. In this incident, O Doleuze was dislodged from SHANTARAAM. O Doleuze was subsequently examined by the Club’s medical officers and cleared to fulfil his remaining race riding engagements.\nSUPREME PROFIT began only fairly.\nApproaching the 1300 Metres, TAI PO FORTUNE blundered when being shifted in behind AMAZING GIFT. TAI PO FORTUNE then got its head up when racing keenly passing the 1000 Metres.\nNear the 800 Metres, COOL PAL was left racing wide and without cover.\nPassing the 300 Metres, SUPREME PROFIT lay in and proved reluctant to shift to the outside of DOUBLE DRAGON. SUPREME PROFIT continued to hang in under pressure and over the concluding stages raced tight outside GOLDWEAVER. Because of this, SUPREME PROFIT was not able to be properly tested over the concluding stages.\nDOUBLE DRAGON and PLAIN BLUE BANNER were sent for sampling.\nAutumn
6713.0CARE FREE ELEGANCEP340C Y HoK L Man1151053125-1/24.03.03.07.01.23.2299NaNNaN2014-00120140914-1.html2014-09-14Sha Tin1Class 51400GOOD TO FIRMTIM WA HANDICAPTURF - "A" COURSE13.59 22.08 23.11 23.55\n When about to enter the track, SHANTARAAM became fractious, reared on two occasions and then threw itself down. SHANTARAAM was examined by Veterinary Officer who said in his opinion it was unsuitable to race. Accordingly, SHANTARAAM was withdrawn by order of the Stewards acting on veterinary advice. Before being allowed to race again, SHANTARAAM will be subjected to an official veterinary examination. In this incident, O Doleuze was dislodged from SHANTARAAM. O Doleuze was subsequently examined by the Club’s medical officers and cleared to fulfil his remaining race riding engagements.\nSUPREME PROFIT began only fairly.\nApproaching the 1300 Metres, TAI PO FORTUNE blundered when being shifted in behind AMAZING GIFT. TAI PO FORTUNE then got its head up when racing keenly passing the 1000 Metres.\nNear the 800 Metres, COOL PAL was left racing wide and without cover.\nPassing the 300 Metres, SUPREME PROFIT lay in and proved reluctant to shift to the outside of DOUBLE DRAGON. SUPREME PROFIT continued to hang in under pressure and over the concluding stages raced tight outside GOLDWEAVER. Because of this, SUPREME PROFIT was not able to be properly tested over the concluding stages.\nDOUBLE DRAGON and PLAIN BLUE BANNER were sent for sampling.\nAutumn
784.0COOL PALS035H W LaiL Ho129120385-3/45.06.06.08.01.23.2521NaNNaN2014-00120140914-1.html2014-09-14Sha Tin1Class 51400GOOD TO FIRMTIM WA HANDICAPTURF - "A" COURSE13.59 22.08 23.11 23.55\n When about to enter the track, SHANTARAAM became fractious, reared on two occasions and then threw itself down. SHANTARAAM was examined by Veterinary Officer who said in his opinion it was unsuitable to race. Accordingly, SHANTARAAM was withdrawn by order of the Stewards acting on veterinary advice. Before being allowed to race again, SHANTARAAM will be subjected to an official veterinary examination. In this incident, O Doleuze was dislodged from SHANTARAAM. O Doleuze was subsequently examined by the Club’s medical officers and cleared to fulfil his remaining race riding engagements.\nSUPREME PROFIT began only fairly.\nApproaching the 1300 Metres, TAI PO FORTUNE blundered when being shifted in behind AMAZING GIFT. TAI PO FORTUNE then got its head up when racing keenly passing the 1000 Metres.\nNear the 800 Metres, COOL PAL was left racing wide and without cover.\nPassing the 300 Metres, SUPREME PROFIT lay in and proved reluctant to shift to the outside of DOUBLE DRAGON. SUPREME PROFIT continued to hang in under pressure and over the concluding stages raced tight outside GOLDWEAVER. Because of this, SUPREME PROFIT was not able to be properly tested over the concluding stages.\nDOUBLE DRAGON and PLAIN BLUE BANNER were sent for sampling.\nAutumn
896.0TAI PO FORTUNEP081K TeetanT P Yung127107366-1/47.07.07.09.01.23.3310NaNNaN2014-00120140914-1.html2014-09-14Sha Tin1Class 51400GOOD TO FIRMTIM WA HANDICAPTURF - "A" COURSE13.59 22.08 23.11 23.55\n When about to enter the track, SHANTARAAM became fractious, reared on two occasions and then threw itself down. SHANTARAAM was examined by Veterinary Officer who said in his opinion it was unsuitable to race. Accordingly, SHANTARAAM was withdrawn by order of the Stewards acting on veterinary advice. Before being allowed to race again, SHANTARAAM will be subjected to an official veterinary examination. In this incident, O Doleuze was dislodged from SHANTARAAM. O Doleuze was subsequently examined by the Club’s medical officers and cleared to fulfil his remaining race riding engagements.\nSUPREME PROFIT began only fairly.\nApproaching the 1300 Metres, TAI PO FORTUNE blundered when being shifted in behind AMAZING GIFT. TAI PO FORTUNE then got its head up when racing keenly passing the 1000 Metres.\nNear the 800 Metres, COOL PAL was left racing wide and without cover.\nPassing the 300 Metres, SUPREME PROFIT lay in and proved reluctant to shift to the outside of DOUBLE DRAGON. SUPREME PROFIT continued to hang in under pressure and over the concluding stages raced tight outside GOLDWEAVER. Because of this, SUPREME PROFIT was not able to be properly tested over the concluding stages.\nDOUBLE DRAGON and PLAIN BLUE BANNER were sent for sampling.\nAutumn
91011.0SUPER HORSEL308T H SoC W Chang119113776-3/411.011.012.010.01.23.4127NaNNaN2014-00120140914-1.html2014-09-14Sha Tin1Class 51400GOOD TO FIRMTIM WA HANDICAPTURF - "A" COURSE13.59 22.08 23.11 23.55\n When about to enter the track, SHANTARAAM became fractious, reared on two occasions and then threw itself down. SHANTARAAM was examined by Veterinary Officer who said in his opinion it was unsuitable to race. Accordingly, SHANTARAAM was withdrawn by order of the Stewards acting on veterinary advice. Before being allowed to race again, SHANTARAAM will be subjected to an official veterinary examination. In this incident, O Doleuze was dislodged from SHANTARAAM. O Doleuze was subsequently examined by the Club’s medical officers and cleared to fulfil his remaining race riding engagements.\nSUPREME PROFIT began only fairly.\nApproaching the 1300 Metres, TAI PO FORTUNE blundered when being shifted in behind AMAZING GIFT. TAI PO FORTUNE then got its head up when racing keenly passing the 1000 Metres.\nNear the 800 Metres, COOL PAL was left racing wide and without cover.\nPassing the 300 Metres, SUPREME PROFIT lay in and proved reluctant to shift to the outside of DOUBLE DRAGON. SUPREME PROFIT continued to hang in under pressure and over the concluding stages raced tight outside GOLDWEAVER. Because of this, SUPREME PROFIT was not able to be properly tested over the concluding stages.\nDOUBLE DRAGON and PLAIN BLUE BANNER were sent for sampling.\nAutumn
finishing_positionhorse_numberhorse_namehorse_idjockeytraineractual_weightdeclared_horse_weightdrawlength_behind_winnerrunning_position_1running_position_2running_position_3running_position_4finish_timewin_oddsrunning_position_5running_position_6race_idsrcrace_daterace_courserace_numberrace_classrace_distancetrack_conditionrace_nametracksectional_timeincident_reportSeason
3017961.0SUNNY WAYV176S ClippertonJ Moore1311053144-1/410.010.010.06.01.23.767.9NaNNaN2016-80520170716-9.html2017-07-16Sha Tin9Class 31400GOOD TO YIELDINGMR AWARD HANDICAPTURF - "C" COURSE13.43 22.23 24.01 23.42\n WINSTON’S LAD was withdrawn on 13.7.17 by order of the Stewards acting on veterinary advice (swollen left front fetlock) and was replaced by Standby Declared Starter MIGHTY BOY. Before being allowed to race again, WINSTON’S LAD will be subjected to an official veterinary examination.\nWhen parading prior to the race, the tongue tie applied to DOUBLE VALENTINE became dislodged with this gear being reapplied behind the barriers.\nJust prior to the start being effected, HEHA BOY became very fractious and lunged at the front gates, resulting in its rider, Apprentice H N Wong, being dislodged and HEHA BOY leaving the barrier stalls riderless. Before being allowed to race again, HEHA BOY will be required to perform satisfactorily in a barrier trial.\nHIGH AND MIGHTY was very slow to begin. A veterinary inspection of HIGH AND MIGHTY immediately following the race found that horse to be lame in its right front leg, however, the horse was unable to be scoped due to being fractious. Having regard to HIGH AND MIGHTY’s previous record of having been slow to begin, the horse will be required to perform satisfactorily in a barrier trial and be subjected to an official veterinary examination before being allowed to race again.\nSUNNY WAY began very awkwardly and shifted in abruptly, resulting in DOUBLE VALENTINE being badly hampered.\nMIGHTY BOY and FANTASTIC KAKA began only fairly.\nPassing the 1200 Metres, MIGHTY BOY was momentarily crowded for room inside INTREPIC (Apprentice M F Poon) which shifted in before being directed back out to relieve the tightening to MIGHTY BOY. Apprentice Poon was advised to exercise more care when shifting ground in similar circumstances.\nApproaching the 1000 Metres, CHUNG WAH SPIRIT was awkwardly placed close to the heels of WORLD RECORD and shifted out away from the heels of that horse. SUNNY WAY, which was racing to the outside of CHUNG WAH SPIRIT, was hampered in consequence.\nNear the 250 Metres, CHUNG WAH SPIRIT commenced to shift in under pressure, resulting in its rider, Z Purton, momentarily having to stop riding and straighten his mount.\nPassing the 100 Metres, WORLD RECORD was shifted in away from the heels of SUNNY WAY which lay in under pressure.\nThroughout the race, SUNNY WAY travelled wide and without cover.\nS Clipperton pleaded guilty to a breach of Rule 100(2) in that he failed to ride SUNNY WAY, 6th placegetter, out all the way to the end of the race to the satisfaction of the Stewards. S Clipperton was fined $15,000.\nCHUNG WAH SPIRIT lost its right front plate after the race.\nWhen questioned regarding the performance of INTREPIC, Apprentice M F Poon stated that the horse travelled well in the early and middle stages and rounding the Home Turn he anticipated the horse would finish off the race strongly after being shifted to the outside of RIGHT HONOURABLE. He said however that passing the 400 Metres INTREPIC did not quicken as it had when ridden by him in the past. He added after this INTREPIC did not finish off the race as he expected and was disappointing over the concluding stages. A veterinary inspection of INTREPIC immediately following the race did not show any significant findings.\nA veterinary inspection of WORLD RECORD immediately following the race did not show any significant findings.\nINTREPIC, CALCULATION and CHUNG WAH SPIRIT were sent for sampling.\n<17/7/2017 Additional Veterinary Report>WORLD RECORD, which performed poorly, was examined by the Veterinary Officer who said at that time there were no significant findings. WORLD RECORD was again examined by the Veterinary Officer at the stables of Trainer A T Millard this morning. He said at this time he noted the horse to be lame in its right front leg. Before being allowed to race again, WORLD RECORD will be subjected to an official veterinary examination.\nSummer
3018079.0GOLDEN SLEEPT117K K ChiongC H Yip1171170104-1/27.02.02.07.01.23.7979NaNNaN2016-80520170716-9.html2017-07-16Sha Tin9Class 31400GOOD TO YIELDINGMR AWARD HANDICAPTURF - "C" COURSE13.43 22.23 24.01 23.42\n WINSTON’S LAD was withdrawn on 13.7.17 by order of the Stewards acting on veterinary advice (swollen left front fetlock) and was replaced by Standby Declared Starter MIGHTY BOY. Before being allowed to race again, WINSTON’S LAD will be subjected to an official veterinary examination.\nWhen parading prior to the race, the tongue tie applied to DOUBLE VALENTINE became dislodged with this gear being reapplied behind the barriers.\nJust prior to the start being effected, HEHA BOY became very fractious and lunged at the front gates, resulting in its rider, Apprentice H N Wong, being dislodged and HEHA BOY leaving the barrier stalls riderless. Before being allowed to race again, HEHA BOY will be required to perform satisfactorily in a barrier trial.\nHIGH AND MIGHTY was very slow to begin. A veterinary inspection of HIGH AND MIGHTY immediately following the race found that horse to be lame in its right front leg, however, the horse was unable to be scoped due to being fractious. Having regard to HIGH AND MIGHTY’s previous record of having been slow to begin, the horse will be required to perform satisfactorily in a barrier trial and be subjected to an official veterinary examination before being allowed to race again.\nSUNNY WAY began very awkwardly and shifted in abruptly, resulting in DOUBLE VALENTINE being badly hampered.\nMIGHTY BOY and FANTASTIC KAKA began only fairly.\nPassing the 1200 Metres, MIGHTY BOY was momentarily crowded for room inside INTREPIC (Apprentice M F Poon) which shifted in before being directed back out to relieve the tightening to MIGHTY BOY. Apprentice Poon was advised to exercise more care when shifting ground in similar circumstances.\nApproaching the 1000 Metres, CHUNG WAH SPIRIT was awkwardly placed close to the heels of WORLD RECORD and shifted out away from the heels of that horse. SUNNY WAY, which was racing to the outside of CHUNG WAH SPIRIT, was hampered in consequence.\nNear the 250 Metres, CHUNG WAH SPIRIT commenced to shift in under pressure, resulting in its rider, Z Purton, momentarily having to stop riding and straighten his mount.\nPassing the 100 Metres, WORLD RECORD was shifted in away from the heels of SUNNY WAY which lay in under pressure.\nThroughout the race, SUNNY WAY travelled wide and without cover.\nS Clipperton pleaded guilty to a breach of Rule 100(2) in that he failed to ride SUNNY WAY, 6th placegetter, out all the way to the end of the race to the satisfaction of the Stewards. S Clipperton was fined $15,000.\nCHUNG WAH SPIRIT lost its right front plate after the race.\nWhen questioned regarding the performance of INTREPIC, Apprentice M F Poon stated that the horse travelled well in the early and middle stages and rounding the Home Turn he anticipated the horse would finish off the race strongly after being shifted to the outside of RIGHT HONOURABLE. He said however that passing the 400 Metres INTREPIC did not quicken as it had when ridden by him in the past. He added after this INTREPIC did not finish off the race as he expected and was disappointing over the concluding stages. A veterinary inspection of INTREPIC immediately following the race did not show any significant findings.\nA veterinary inspection of WORLD RECORD immediately following the race did not show any significant findings.\nINTREPIC, CALCULATION and CHUNG WAH SPIRIT were sent for sampling.\n<17/7/2017 Additional Veterinary Report>WORLD RECORD, which performed poorly, was examined by the Veterinary Officer who said at that time there were no significant findings. WORLD RECORD was again examined by the Veterinary Officer at the stables of Trainer A T Millard this morning. He said at this time he noted the horse to be lame in its right front leg. Before being allowed to race again, WORLD RECORD will be subjected to an official veterinary examination.\nSummer
3018186.0WORLD RECORDV040C MurrayA T Millard127107345-1/24.07.07.08.01.23.988.4NaNNaN2016-80520170716-9.html2017-07-16Sha Tin9Class 31400GOOD TO YIELDINGMR AWARD HANDICAPTURF - "C" COURSE13.43 22.23 24.01 23.42\n WINSTON’S LAD was withdrawn on 13.7.17 by order of the Stewards acting on veterinary advice (swollen left front fetlock) and was replaced by Standby Declared Starter MIGHTY BOY. Before being allowed to race again, WINSTON’S LAD will be subjected to an official veterinary examination.\nWhen parading prior to the race, the tongue tie applied to DOUBLE VALENTINE became dislodged with this gear being reapplied behind the barriers.\nJust prior to the start being effected, HEHA BOY became very fractious and lunged at the front gates, resulting in its rider, Apprentice H N Wong, being dislodged and HEHA BOY leaving the barrier stalls riderless. Before being allowed to race again, HEHA BOY will be required to perform satisfactorily in a barrier trial.\nHIGH AND MIGHTY was very slow to begin. A veterinary inspection of HIGH AND MIGHTY immediately following the race found that horse to be lame in its right front leg, however, the horse was unable to be scoped due to being fractious. Having regard to HIGH AND MIGHTY’s previous record of having been slow to begin, the horse will be required to perform satisfactorily in a barrier trial and be subjected to an official veterinary examination before being allowed to race again.\nSUNNY WAY began very awkwardly and shifted in abruptly, resulting in DOUBLE VALENTINE being badly hampered.\nMIGHTY BOY and FANTASTIC KAKA began only fairly.\nPassing the 1200 Metres, MIGHTY BOY was momentarily crowded for room inside INTREPIC (Apprentice M F Poon) which shifted in before being directed back out to relieve the tightening to MIGHTY BOY. Apprentice Poon was advised to exercise more care when shifting ground in similar circumstances.\nApproaching the 1000 Metres, CHUNG WAH SPIRIT was awkwardly placed close to the heels of WORLD RECORD and shifted out away from the heels of that horse. SUNNY WAY, which was racing to the outside of CHUNG WAH SPIRIT, was hampered in consequence.\nNear the 250 Metres, CHUNG WAH SPIRIT commenced to shift in under pressure, resulting in its rider, Z Purton, momentarily having to stop riding and straighten his mount.\nPassing the 100 Metres, WORLD RECORD was shifted in away from the heels of SUNNY WAY which lay in under pressure.\nThroughout the race, SUNNY WAY travelled wide and without cover.\nS Clipperton pleaded guilty to a breach of Rule 100(2) in that he failed to ride SUNNY WAY, 6th placegetter, out all the way to the end of the race to the satisfaction of the Stewards. S Clipperton was fined $15,000.\nCHUNG WAH SPIRIT lost its right front plate after the race.\nWhen questioned regarding the performance of INTREPIC, Apprentice M F Poon stated that the horse travelled well in the early and middle stages and rounding the Home Turn he anticipated the horse would finish off the race strongly after being shifted to the outside of RIGHT HONOURABLE. He said however that passing the 400 Metres INTREPIC did not quicken as it had when ridden by him in the past. He added after this INTREPIC did not finish off the race as he expected and was disappointing over the concluding stages. A veterinary inspection of INTREPIC immediately following the race did not show any significant findings.\nA veterinary inspection of WORLD RECORD immediately following the race did not show any significant findings.\nINTREPIC, CALCULATION and CHUNG WAH SPIRIT were sent for sampling.\n<17/7/2017 Additional Veterinary Report>WORLD RECORD, which performed poorly, was examined by the Veterinary Officer who said at that time there were no significant findings. WORLD RECORD was again examined by the Veterinary Officer at the stables of Trainer A T Millard this morning. He said at this time he noted the horse to be lame in its right front leg. Before being allowed to race again, WORLD RECORD will be subjected to an official veterinary examination.\nSummer
3018297.0INTREPICA139M F PoonD J Hall116993262.04.05.09.01.24.054NaNNaN2016-80520170716-9.html2017-07-16Sha Tin9Class 31400GOOD TO YIELDINGMR AWARD HANDICAPTURF - "C" COURSE13.43 22.23 24.01 23.42\n WINSTON’S LAD was withdrawn on 13.7.17 by order of the Stewards acting on veterinary advice (swollen left front fetlock) and was replaced by Standby Declared Starter MIGHTY BOY. Before being allowed to race again, WINSTON’S LAD will be subjected to an official veterinary examination.\nWhen parading prior to the race, the tongue tie applied to DOUBLE VALENTINE became dislodged with this gear being reapplied behind the barriers.\nJust prior to the start being effected, HEHA BOY became very fractious and lunged at the front gates, resulting in its rider, Apprentice H N Wong, being dislodged and HEHA BOY leaving the barrier stalls riderless. Before being allowed to race again, HEHA BOY will be required to perform satisfactorily in a barrier trial.\nHIGH AND MIGHTY was very slow to begin. A veterinary inspection of HIGH AND MIGHTY immediately following the race found that horse to be lame in its right front leg, however, the horse was unable to be scoped due to being fractious. Having regard to HIGH AND MIGHTY’s previous record of having been slow to begin, the horse will be required to perform satisfactorily in a barrier trial and be subjected to an official veterinary examination before being allowed to race again.\nSUNNY WAY began very awkwardly and shifted in abruptly, resulting in DOUBLE VALENTINE being badly hampered.\nMIGHTY BOY and FANTASTIC KAKA began only fairly.\nPassing the 1200 Metres, MIGHTY BOY was momentarily crowded for room inside INTREPIC (Apprentice M F Poon) which shifted in before being directed back out to relieve the tightening to MIGHTY BOY. Apprentice Poon was advised to exercise more care when shifting ground in similar circumstances.\nApproaching the 1000 Metres, CHUNG WAH SPIRIT was awkwardly placed close to the heels of WORLD RECORD and shifted out away from the heels of that horse. SUNNY WAY, which was racing to the outside of CHUNG WAH SPIRIT, was hampered in consequence.\nNear the 250 Metres, CHUNG WAH SPIRIT commenced to shift in under pressure, resulting in its rider, Z Purton, momentarily having to stop riding and straighten his mount.\nPassing the 100 Metres, WORLD RECORD was shifted in away from the heels of SUNNY WAY which lay in under pressure.\nThroughout the race, SUNNY WAY travelled wide and without cover.\nS Clipperton pleaded guilty to a breach of Rule 100(2) in that he failed to ride SUNNY WAY, 6th placegetter, out all the way to the end of the race to the satisfaction of the Stewards. S Clipperton was fined $15,000.\nCHUNG WAH SPIRIT lost its right front plate after the race.\nWhen questioned regarding the performance of INTREPIC, Apprentice M F Poon stated that the horse travelled well in the early and middle stages and rounding the Home Turn he anticipated the horse would finish off the race strongly after being shifted to the outside of RIGHT HONOURABLE. He said however that passing the 400 Metres INTREPIC did not quicken as it had when ridden by him in the past. He added after this INTREPIC did not finish off the race as he expected and was disappointing over the concluding stages. A veterinary inspection of INTREPIC immediately following the race did not show any significant findings.\nA veterinary inspection of WORLD RECORD immediately following the race did not show any significant findings.\nINTREPIC, CALCULATION and CHUNG WAH SPIRIT were sent for sampling.\n<17/7/2017 Additional Veterinary Report>WORLD RECORD, which performed poorly, was examined by the Veterinary Officer who said at that time there were no significant findings. WORLD RECORD was again examined by the Veterinary Officer at the stables of Trainer A T Millard this morning. He said at this time he noted the horse to be lame in its right front leg. Before being allowed to race again, WORLD RECORD will be subjected to an official veterinary examination.\nSummer
301831012.0HIGH AND MIGHTYS362D WhyteW Y So1191132116-3/412.012.011.010.01.24.187.2NaNNaN2016-80520170716-9.html2017-07-16Sha Tin9Class 31400GOOD TO YIELDINGMR AWARD HANDICAPTURF - "C" COURSE13.43 22.23 24.01 23.42\n WINSTON’S LAD was withdrawn on 13.7.17 by order of the Stewards acting on veterinary advice (swollen left front fetlock) and was replaced by Standby Declared Starter MIGHTY BOY. Before being allowed to race again, WINSTON’S LAD will be subjected to an official veterinary examination.\nWhen parading prior to the race, the tongue tie applied to DOUBLE VALENTINE became dislodged with this gear being reapplied behind the barriers.\nJust prior to the start being effected, HEHA BOY became very fractious and lunged at the front gates, resulting in its rider, Apprentice H N Wong, being dislodged and HEHA BOY leaving the barrier stalls riderless. Before being allowed to race again, HEHA BOY will be required to perform satisfactorily in a barrier trial.\nHIGH AND MIGHTY was very slow to begin. A veterinary inspection of HIGH AND MIGHTY immediately following the race found that horse to be lame in its right front leg, however, the horse was unable to be scoped due to being fractious. Having regard to HIGH AND MIGHTY’s previous record of having been slow to begin, the horse will be required to perform satisfactorily in a barrier trial and be subjected to an official veterinary examination before being allowed to race again.\nSUNNY WAY began very awkwardly and shifted in abruptly, resulting in DOUBLE VALENTINE being badly hampered.\nMIGHTY BOY and FANTASTIC KAKA began only fairly.\nPassing the 1200 Metres, MIGHTY BOY was momentarily crowded for room inside INTREPIC (Apprentice M F Poon) which shifted in before being directed back out to relieve the tightening to MIGHTY BOY. Apprentice Poon was advised to exercise more care when shifting ground in similar circumstances.\nApproaching the 1000 Metres, CHUNG WAH SPIRIT was awkwardly placed close to the heels of WORLD RECORD and shifted out away from the heels of that horse. SUNNY WAY, which was racing to the outside of CHUNG WAH SPIRIT, was hampered in consequence.\nNear the 250 Metres, CHUNG WAH SPIRIT commenced to shift in under pressure, resulting in its rider, Z Purton, momentarily having to stop riding and straighten his mount.\nPassing the 100 Metres, WORLD RECORD was shifted in away from the heels of SUNNY WAY which lay in under pressure.\nThroughout the race, SUNNY WAY travelled wide and without cover.\nS Clipperton pleaded guilty to a breach of Rule 100(2) in that he failed to ride SUNNY WAY, 6th placegetter, out all the way to the end of the race to the satisfaction of the Stewards. S Clipperton was fined $15,000.\nCHUNG WAH SPIRIT lost its right front plate after the race.\nWhen questioned regarding the performance of INTREPIC, Apprentice M F Poon stated that the horse travelled well in the early and middle stages and rounding the Home Turn he anticipated the horse would finish off the race strongly after being shifted to the outside of RIGHT HONOURABLE. He said however that passing the 400 Metres INTREPIC did not quicken as it had when ridden by him in the past. He added after this INTREPIC did not finish off the race as he expected and was disappointing over the concluding stages. A veterinary inspection of INTREPIC immediately following the race did not show any significant findings.\nA veterinary inspection of WORLD RECORD immediately following the race did not show any significant findings.\nINTREPIC, CALCULATION and CHUNG WAH SPIRIT were sent for sampling.\n<17/7/2017 Additional Veterinary Report>WORLD RECORD, which performed poorly, was examined by the Veterinary Officer who said at that time there were no significant findings. WORLD RECORD was again examined by the Veterinary Officer at the stables of Trainer A T Millard this morning. He said at this time he noted the horse to be lame in its right front leg. Before being allowed to race again, WORLD RECORD will be subjected to an official veterinary examination.\nSummer
30184113.0DOUBLE VALENTINEA163B PrebbleA S Cruz1271085139-1/411.011.012.011.01.24.5841NaNNaN2016-80520170716-9.html2017-07-16Sha Tin9Class 31400GOOD TO YIELDINGMR AWARD HANDICAPTURF - "C" COURSE13.43 22.23 24.01 23.42\n WINSTON’S LAD was withdrawn on 13.7.17 by order of the Stewards acting on veterinary advice (swollen left front fetlock) and was replaced by Standby Declared Starter MIGHTY BOY. Before being allowed to race again, WINSTON’S LAD will be subjected to an official veterinary examination.\nWhen parading prior to the race, the tongue tie applied to DOUBLE VALENTINE became dislodged with this gear being reapplied behind the barriers.\nJust prior to the start being effected, HEHA BOY became very fractious and lunged at the front gates, resulting in its rider, Apprentice H N Wong, being dislodged and HEHA BOY leaving the barrier stalls riderless. Before being allowed to race again, HEHA BOY will be required to perform satisfactorily in a barrier trial.\nHIGH AND MIGHTY was very slow to begin. A veterinary inspection of HIGH AND MIGHTY immediately following the race found that horse to be lame in its right front leg, however, the horse was unable to be scoped due to being fractious. Having regard to HIGH AND MIGHTY’s previous record of having been slow to begin, the horse will be required to perform satisfactorily in a barrier trial and be subjected to an official veterinary examination before being allowed to race again.\nSUNNY WAY began very awkwardly and shifted in abruptly, resulting in DOUBLE VALENTINE being badly hampered.\nMIGHTY BOY and FANTASTIC KAKA began only fairly.\nPassing the 1200 Metres, MIGHTY BOY was momentarily crowded for room inside INTREPIC (Apprentice M F Poon) which shifted in before being directed back out to relieve the tightening to MIGHTY BOY. Apprentice Poon was advised to exercise more care when shifting ground in similar circumstances.\nApproaching the 1000 Metres, CHUNG WAH SPIRIT was awkwardly placed close to the heels of WORLD RECORD and shifted out away from the heels of that horse. SUNNY WAY, which was racing to the outside of CHUNG WAH SPIRIT, was hampered in consequence.\nNear the 250 Metres, CHUNG WAH SPIRIT commenced to shift in under pressure, resulting in its rider, Z Purton, momentarily having to stop riding and straighten his mount.\nPassing the 100 Metres, WORLD RECORD was shifted in away from the heels of SUNNY WAY which lay in under pressure.\nThroughout the race, SUNNY WAY travelled wide and without cover.\nS Clipperton pleaded guilty to a breach of Rule 100(2) in that he failed to ride SUNNY WAY, 6th placegetter, out all the way to the end of the race to the satisfaction of the Stewards. S Clipperton was fined $15,000.\nCHUNG WAH SPIRIT lost its right front plate after the race.\nWhen questioned regarding the performance of INTREPIC, Apprentice M F Poon stated that the horse travelled well in the early and middle stages and rounding the Home Turn he anticipated the horse would finish off the race strongly after being shifted to the outside of RIGHT HONOURABLE. He said however that passing the 400 Metres INTREPIC did not quicken as it had when ridden by him in the past. He added after this INTREPIC did not finish off the race as he expected and was disappointing over the concluding stages. A veterinary inspection of INTREPIC immediately following the race did not show any significant findings.\nA veterinary inspection of WORLD RECORD immediately following the race did not show any significant findings.\nINTREPIC, CALCULATION and CHUNG WAH SPIRIT were sent for sampling.\n<17/7/2017 Additional Veterinary Report>WORLD RECORD, which performed poorly, was examined by the Veterinary Officer who said at that time there were no significant findings. WORLD RECORD was again examined by the Veterinary Officer at the stables of Trainer A T Millard this morning. He said at this time he noted the horse to be lame in its right front leg. Before being allowed to race again, WORLD RECORD will be subjected to an official veterinary examination.\nSummer
30185128.0THE JOY OF GIVINGA249W M LaiC W Chang1221026913-1/213.013.013.012.01.25.2699NaNNaN2016-80520170716-9.html2017-07-16Sha Tin9Class 31400GOOD TO YIELDINGMR AWARD HANDICAPTURF - "C" COURSE13.43 22.23 24.01 23.42\n WINSTON’S LAD was withdrawn on 13.7.17 by order of the Stewards acting on veterinary advice (swollen left front fetlock) and was replaced by Standby Declared Starter MIGHTY BOY. Before being allowed to race again, WINSTON’S LAD will be subjected to an official veterinary examination.\nWhen parading prior to the race, the tongue tie applied to DOUBLE VALENTINE became dislodged with this gear being reapplied behind the barriers.\nJust prior to the start being effected, HEHA BOY became very fractious and lunged at the front gates, resulting in its rider, Apprentice H N Wong, being dislodged and HEHA BOY leaving the barrier stalls riderless. Before being allowed to race again, HEHA BOY will be required to perform satisfactorily in a barrier trial.\nHIGH AND MIGHTY was very slow to begin. A veterinary inspection of HIGH AND MIGHTY immediately following the race found that horse to be lame in its right front leg, however, the horse was unable to be scoped due to being fractious. Having regard to HIGH AND MIGHTY’s previous record of having been slow to begin, the horse will be required to perform satisfactorily in a barrier trial and be subjected to an official veterinary examination before being allowed to race again.\nSUNNY WAY began very awkwardly and shifted in abruptly, resulting in DOUBLE VALENTINE being badly hampered.\nMIGHTY BOY and FANTASTIC KAKA began only fairly.\nPassing the 1200 Metres, MIGHTY BOY was momentarily crowded for room inside INTREPIC (Apprentice M F Poon) which shifted in before being directed back out to relieve the tightening to MIGHTY BOY. Apprentice Poon was advised to exercise more care when shifting ground in similar circumstances.\nApproaching the 1000 Metres, CHUNG WAH SPIRIT was awkwardly placed close to the heels of WORLD RECORD and shifted out away from the heels of that horse. SUNNY WAY, which was racing to the outside of CHUNG WAH SPIRIT, was hampered in consequence.\nNear the 250 Metres, CHUNG WAH SPIRIT commenced to shift in under pressure, resulting in its rider, Z Purton, momentarily having to stop riding and straighten his mount.\nPassing the 100 Metres, WORLD RECORD was shifted in away from the heels of SUNNY WAY which lay in under pressure.\nThroughout the race, SUNNY WAY travelled wide and without cover.\nS Clipperton pleaded guilty to a breach of Rule 100(2) in that he failed to ride SUNNY WAY, 6th placegetter, out all the way to the end of the race to the satisfaction of the Stewards. S Clipperton was fined $15,000.\nCHUNG WAH SPIRIT lost its right front plate after the race.\nWhen questioned regarding the performance of INTREPIC, Apprentice M F Poon stated that the horse travelled well in the early and middle stages and rounding the Home Turn he anticipated the horse would finish off the race strongly after being shifted to the outside of RIGHT HONOURABLE. He said however that passing the 400 Metres INTREPIC did not quicken as it had when ridden by him in the past. He added after this INTREPIC did not finish off the race as he expected and was disappointing over the concluding stages. A veterinary inspection of INTREPIC immediately following the race did not show any significant findings.\nA veterinary inspection of WORLD RECORD immediately following the race did not show any significant findings.\nINTREPIC, CALCULATION and CHUNG WAH SPIRIT were sent for sampling.\n<17/7/2017 Additional Veterinary Report>WORLD RECORD, which performed poorly, was examined by the Veterinary Officer who said at that time there were no significant findings. WORLD RECORD was again examined by the Veterinary Officer at the stables of Trainer A T Millard this morning. He said at this time he noted the horse to be lame in its right front leg. Before being allowed to race again, WORLD RECORD will be subjected to an official veterinary examination.\nSummer
30186135.0MIGHTY BOYA352N CallanJ Moore1261153114-1/45.05.04.013.01.25.3541NaNNaN2016-80520170716-9.html2017-07-16Sha Tin9Class 31400GOOD TO YIELDINGMR AWARD HANDICAPTURF - "C" COURSE13.43 22.23 24.01 23.42\n WINSTON’S LAD was withdrawn on 13.7.17 by order of the Stewards acting on veterinary advice (swollen left front fetlock) and was replaced by Standby Declared Starter MIGHTY BOY. Before being allowed to race again, WINSTON’S LAD will be subjected to an official veterinary examination.\nWhen parading prior to the race, the tongue tie applied to DOUBLE VALENTINE became dislodged with this gear being reapplied behind the barriers.\nJust prior to the start being effected, HEHA BOY became very fractious and lunged at the front gates, resulting in its rider, Apprentice H N Wong, being dislodged and HEHA BOY leaving the barrier stalls riderless. Before being allowed to race again, HEHA BOY will be required to perform satisfactorily in a barrier trial.\nHIGH AND MIGHTY was very slow to begin. A veterinary inspection of HIGH AND MIGHTY immediately following the race found that horse to be lame in its right front leg, however, the horse was unable to be scoped due to being fractious. Having regard to HIGH AND MIGHTY’s previous record of having been slow to begin, the horse will be required to perform satisfactorily in a barrier trial and be subjected to an official veterinary examination before being allowed to race again.\nSUNNY WAY began very awkwardly and shifted in abruptly, resulting in DOUBLE VALENTINE being badly hampered.\nMIGHTY BOY and FANTASTIC KAKA began only fairly.\nPassing the 1200 Metres, MIGHTY BOY was momentarily crowded for room inside INTREPIC (Apprentice M F Poon) which shifted in before being directed back out to relieve the tightening to MIGHTY BOY. Apprentice Poon was advised to exercise more care when shifting ground in similar circumstances.\nApproaching the 1000 Metres, CHUNG WAH SPIRIT was awkwardly placed close to the heels of WORLD RECORD and shifted out away from the heels of that horse. SUNNY WAY, which was racing to the outside of CHUNG WAH SPIRIT, was hampered in consequence.\nNear the 250 Metres, CHUNG WAH SPIRIT commenced to shift in under pressure, resulting in its rider, Z Purton, momentarily having to stop riding and straighten his mount.\nPassing the 100 Metres, WORLD RECORD was shifted in away from the heels of SUNNY WAY which lay in under pressure.\nThroughout the race, SUNNY WAY travelled wide and without cover.\nS Clipperton pleaded guilty to a breach of Rule 100(2) in that he failed to ride SUNNY WAY, 6th placegetter, out all the way to the end of the race to the satisfaction of the Stewards. S Clipperton was fined $15,000.\nCHUNG WAH SPIRIT lost its right front plate after the race.\nWhen questioned regarding the performance of INTREPIC, Apprentice M F Poon stated that the horse travelled well in the early and middle stages and rounding the Home Turn he anticipated the horse would finish off the race strongly after being shifted to the outside of RIGHT HONOURABLE. He said however that passing the 400 Metres INTREPIC did not quicken as it had when ridden by him in the past. He added after this INTREPIC did not finish off the race as he expected and was disappointing over the concluding stages. A veterinary inspection of INTREPIC immediately following the race did not show any significant findings.\nA veterinary inspection of WORLD RECORD immediately following the race did not show any significant findings.\nINTREPIC, CALCULATION and CHUNG WAH SPIRIT were sent for sampling.\n<17/7/2017 Additional Veterinary Report>WORLD RECORD, which performed poorly, was examined by the Veterinary Officer who said at that time there were no significant findings. WORLD RECORD was again examined by the Veterinary Officer at the stables of Trainer A T Millard this morning. He said at this time he noted the horse to be lame in its right front leg. Before being allowed to race again, WORLD RECORD will be subjected to an official veterinary examination.\nSummer
30187WVNaNWINSTON'S LADT348N CallanK W Lui127-------NaNNaNNaNNaN------NaNNaN2016-80520170716-9.html2017-07-16Sha Tin9Class 31400GOOD TO YIELDINGMR AWARD HANDICAPTURF - "C" COURSE13.43 22.23 24.01 23.42\n WINSTON’S LAD was withdrawn on 13.7.17 by order of the Stewards acting on veterinary advice (swollen left front fetlock) and was replaced by Standby Declared Starter MIGHTY BOY. Before being allowed to race again, WINSTON’S LAD will be subjected to an official veterinary examination.\nWhen parading prior to the race, the tongue tie applied to DOUBLE VALENTINE became dislodged with this gear being reapplied behind the barriers.\nJust prior to the start being effected, HEHA BOY became very fractious and lunged at the front gates, resulting in its rider, Apprentice H N Wong, being dislodged and HEHA BOY leaving the barrier stalls riderless. Before being allowed to race again, HEHA BOY will be required to perform satisfactorily in a barrier trial.\nHIGH AND MIGHTY was very slow to begin. A veterinary inspection of HIGH AND MIGHTY immediately following the race found that horse to be lame in its right front leg, however, the horse was unable to be scoped due to being fractious. Having regard to HIGH AND MIGHTY’s previous record of having been slow to begin, the horse will be required to perform satisfactorily in a barrier trial and be subjected to an official veterinary examination before being allowed to race again.\nSUNNY WAY began very awkwardly and shifted in abruptly, resulting in DOUBLE VALENTINE being badly hampered.\nMIGHTY BOY and FANTASTIC KAKA began only fairly.\nPassing the 1200 Metres, MIGHTY BOY was momentarily crowded for room inside INTREPIC (Apprentice M F Poon) which shifted in before being directed back out to relieve the tightening to MIGHTY BOY. Apprentice Poon was advised to exercise more care when shifting ground in similar circumstances.\nApproaching the 1000 Metres, CHUNG WAH SPIRIT was awkwardly placed close to the heels of WORLD RECORD and shifted out away from the heels of that horse. SUNNY WAY, which was racing to the outside of CHUNG WAH SPIRIT, was hampered in consequence.\nNear the 250 Metres, CHUNG WAH SPIRIT commenced to shift in under pressure, resulting in its rider, Z Purton, momentarily having to stop riding and straighten his mount.\nPassing the 100 Metres, WORLD RECORD was shifted in away from the heels of SUNNY WAY which lay in under pressure.\nThroughout the race, SUNNY WAY travelled wide and without cover.\nS Clipperton pleaded guilty to a breach of Rule 100(2) in that he failed to ride SUNNY WAY, 6th placegetter, out all the way to the end of the race to the satisfaction of the Stewards. S Clipperton was fined $15,000.\nCHUNG WAH SPIRIT lost its right front plate after the race.\nWhen questioned regarding the performance of INTREPIC, Apprentice M F Poon stated that the horse travelled well in the early and middle stages and rounding the Home Turn he anticipated the horse would finish off the race strongly after being shifted to the outside of RIGHT HONOURABLE. He said however that passing the 400 Metres INTREPIC did not quicken as it had when ridden by him in the past. He added after this INTREPIC did not finish off the race as he expected and was disappointing over the concluding stages. A veterinary inspection of INTREPIC immediately following the race did not show any significant findings.\nA veterinary inspection of WORLD RECORD immediately following the race did not show any significant findings.\nINTREPIC, CALCULATION and CHUNG WAH SPIRIT were sent for sampling.\n<17/7/2017 Additional Veterinary Report>WORLD RECORD, which performed poorly, was examined by the Veterinary Officer who said at that time there were no significant findings. WORLD RECORD was again examined by the Veterinary Officer at the stables of Trainer A T Millard this morning. He said at this time he noted the horse to be lame in its right front leg. Before being allowed to race again, WORLD RECORD will be subjected to an official veterinary examination.\nSummer
30188UR13.0HEHA BOYA232H N WongY S Tsui113104012-NaNNaNNaNNaN---99NaNNaN2016-80520170716-9.html2017-07-16Sha Tin9Class 31400GOOD TO YIELDINGMR AWARD HANDICAPTURF - "C" COURSE13.43 22.23 24.01 23.42\n WINSTON’S LAD was withdrawn on 13.7.17 by order of the Stewards acting on veterinary advice (swollen left front fetlock) and was replaced by Standby Declared Starter MIGHTY BOY. Before being allowed to race again, WINSTON’S LAD will be subjected to an official veterinary examination.\nWhen parading prior to the race, the tongue tie applied to DOUBLE VALENTINE became dislodged with this gear being reapplied behind the barriers.\nJust prior to the start being effected, HEHA BOY became very fractious and lunged at the front gates, resulting in its rider, Apprentice H N Wong, being dislodged and HEHA BOY leaving the barrier stalls riderless. Before being allowed to race again, HEHA BOY will be required to perform satisfactorily in a barrier trial.\nHIGH AND MIGHTY was very slow to begin. A veterinary inspection of HIGH AND MIGHTY immediately following the race found that horse to be lame in its right front leg, however, the horse was unable to be scoped due to being fractious. Having regard to HIGH AND MIGHTY’s previous record of having been slow to begin, the horse will be required to perform satisfactorily in a barrier trial and be subjected to an official veterinary examination before being allowed to race again.\nSUNNY WAY began very awkwardly and shifted in abruptly, resulting in DOUBLE VALENTINE being badly hampered.\nMIGHTY BOY and FANTASTIC KAKA began only fairly.\nPassing the 1200 Metres, MIGHTY BOY was momentarily crowded for room inside INTREPIC (Apprentice M F Poon) which shifted in before being directed back out to relieve the tightening to MIGHTY BOY. Apprentice Poon was advised to exercise more care when shifting ground in similar circumstances.\nApproaching the 1000 Metres, CHUNG WAH SPIRIT was awkwardly placed close to the heels of WORLD RECORD and shifted out away from the heels of that horse. SUNNY WAY, which was racing to the outside of CHUNG WAH SPIRIT, was hampered in consequence.\nNear the 250 Metres, CHUNG WAH SPIRIT commenced to shift in under pressure, resulting in its rider, Z Purton, momentarily having to stop riding and straighten his mount.\nPassing the 100 Metres, WORLD RECORD was shifted in away from the heels of SUNNY WAY which lay in under pressure.\nThroughout the race, SUNNY WAY travelled wide and without cover.\nS Clipperton pleaded guilty to a breach of Rule 100(2) in that he failed to ride SUNNY WAY, 6th placegetter, out all the way to the end of the race to the satisfaction of the Stewards. S Clipperton was fined $15,000.\nCHUNG WAH SPIRIT lost its right front plate after the race.\nWhen questioned regarding the performance of INTREPIC, Apprentice M F Poon stated that the horse travelled well in the early and middle stages and rounding the Home Turn he anticipated the horse would finish off the race strongly after being shifted to the outside of RIGHT HONOURABLE. He said however that passing the 400 Metres INTREPIC did not quicken as it had when ridden by him in the past. He added after this INTREPIC did not finish off the race as he expected and was disappointing over the concluding stages. A veterinary inspection of INTREPIC immediately following the race did not show any significant findings.\nA veterinary inspection of WORLD RECORD immediately following the race did not show any significant findings.\nINTREPIC, CALCULATION and CHUNG WAH SPIRIT were sent for sampling.\n<17/7/2017 Additional Veterinary Report>WORLD RECORD, which performed poorly, was examined by the Veterinary Officer who said at that time there were no significant findings. WORLD RECORD was again examined by the Veterinary Officer at the stables of Trainer A T Millard this morning. He said at this time he noted the horse to be lame in its right front leg. Before being allowed to race again, WORLD RECORD will be subjected to an official veterinary examination.\nSummer